Credit Acceptance Corporation
San Francisco, California
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
11/14/2026
Full time
At Credit Acceptance, we are building on the foundation of a successful business while investing in the future through technology, data, AI, and continuous improvement. As we continue to evolve, our Team Members play an active role in improving experiences, driving meaningful change, and shaping the future of our business. We foster an environment where people are empowered to contribute ideas, develop their careers, make an impact, and help lead our continued transformation. Our Engineering teams are helping shape the future of Credit Acceptance through innovation. Team Members collaborate across the organization to solve complex challenges, build impactful solutions, challenge the status quo, and support informed business decisions. We value curiosity, continuous learning, and new ideas from people who are passionate about driving modernization and meaningful business impact. Credit Acceptance makes vehicle ownership possible for consumers other lenders decline, through a dealer network, an originations and servicing platform, and pricing and decisioning models refined over decades. The technology estate underneath this business was built project by project over a long period, and modernizing it is the largest engineering opportunity at the company. As the Distinguished Engineer, you are the senior-most individual contributor in Technology, reporting directly to the Chief Technology Officer. You will set the multi-year technical strategy for the company while staying close enough to the code and systems to remain credible - this is not an architect role that reviews designs from a distance, nor a strong engineer role that goes deep in a single domain. Two things sit at the center of the job: the target architecture for the enterprise, and the architecture for running AI agents across it. You will not own a team; you will own the hardest technical problems the company has, and get them resolved by convincing the people who do own the teams. Outcomes and Activities Enterprise target architecture: Convene the principal and staff engineers who own each domain to define the end-state architecture across originations, servicing, marketplace, data, and AI, and use it to drive the multi-year plan. Ensure every component has a defined interface with stated inputs and outputs, every unmade decision has a written principle standing in for it, and the document states honestly how close the organization is to the end state. Publish the architecture, including the tradeoffs that were rejected and why. Agentic AI architecture across the enterprise: Own the enterprise agent architecture spanning servicing and collections, the dealer side, originations, and internal engineering and back-office workflows, built on one common foundation rather than one stack per team. Establish a governed way for agents to discover and call business capabilities, data, and tools, using the Model Context Protocol as the integration layer. Define an identity and authorization model that treats an agent as a first-class actor with its own least-privilege entitlements, along with observability, evaluation, and cost controls that work consistently for every agent. Set policy on what an agent may decide independently versus what stays with a person, and define where that line moves and on what evidence. Design the architecture to produce an examiner-ready record of what each agent saw, recommended, and touched, and set the evaluation and adversarial testing approach that makes agent outcomes defensible. Ensure the same foundation and controls apply to agents built by outside firms on the company's behalf. Migration off on-premises infrastructure: Own the technical strategy for migrating transactional and analytical workloads off on-premises infrastructure to the company's strategic targets - AWS for transactional workloads and Databricks for analytical workloads - determining what lifts and shifts, what replatforms, what gets re-architected on the way versus after, and what the steady-state cost looks like. Own the resilience and recovery architecture for the target state. Data platform architecture: Set the architecture for change-data-capture-based ingestion, streaming where warranted, and a modern warehouse with no job-scheduling dependency, moving the organization from largely batch analytical data movement to real time. Help settle the open question of who owns the transactional and analytical data models. Real-time decisioning, model serving, and experimentation: Architect for pricing and credit model and scorecard updates that drop in as a layer rather than requiring a multi-quarter rebuild, and for an experimentation platform that supports orders of magnitude more concurrent experiments than a conventional release process allows. Marketplace and search architecture: Own the architecture and interfaces for a unified vehicle inventory, consumer search, and lead routing platform, ensuring the data model supports more than one class of seller from the start. AI-native engineering practice: Define the golden path for how software is specified, generated, reviewed, tested, and deployed, including the analyzers and gates that enforce it, and measure the inputs to that practice rather than just the outputs. Hold the build-versus-buy bar for AI capability, building what is core competency and about to scale, and renting the rest. Performance and peak readiness: Own the instrumentation, baseline, and remediation architecture needed to meet the standard that no page takes more than one second. Own peak-event headroom, including understanding the limits of each system and maintaining tested degradation levers ahead of need. Operating approach: Move the organization from project-shaped systems toward owned platforms with stated contracts. Document every component's inputs and outputs, and be ready to argue why closely coupled components should not be consolidated into one. Work toward a two-week requirement-to-production iteration bar, treating architecture that cannot be delivered incrementally as unfinished. Name what comes off the plan whenever a change in direction is requested. Make the call and own the outcome on architectural recommendations. Treat security, privacy, auditability, and regulatory obligation as design inputs from the start in this regulated environment. Hands-on, not hands-off: This is not optional. Stay personally engaged in the technical work rather than directing it from a distance. Join design reviews, write proofs of concept, read code, and engage in incident analysis. This hands-on time does not replace the work the teams own, and it is not a fallback when delivery slips. Every engineer in the organization will read how you write, how you argue a design, how you handle being wrong, and how you treat engineers who disagree with you as the bar. Staff and principal engineers should be measurably better at this work for having worked with you. Success measures: A published target architecture the domain owners agree with and that the annual and long-range plans are actually written against; an enterprise agent foundation that internal teams and partners build on, with access controls, evaluation, and audit records in place; a credible, dated, costed migration path off on-premises infrastructure and demonstrated progress against it; measured improvement in chosen input metrics such as latency, availability, recovery objectives, deployment frequency, and experiment throughput; growth in the number of principal and staff engineers who are better at this work as a result of this role; and architectural decisions that stop being relitigated because the reasoning was written down and the interfaces were clear. Competencies Customer Empathy: Customer Empathy is the ability to understand the perspectives, pain points, and experiences of customers. It involves actively putting oneself in the customer's shoes, comprehending their needs and challenges, and using that understanding to provide a better, more customer-centric experience. Engineering Excellence: Engineering Excellence is about bringing great craftsmanship and thought leadership to deliver an outstanding product that delights customers and solves for the business. This involves the pursuit and achievement of high standards, best practices, innovation, and superior solutions. One Team: A One Team mindset refers to a collaborative approach across the organization, where individuals work together seamlessly, without boundaries, as a single, cohesive team. Shared goals, open communication and mutual support create a sense of collective purpose. This enables teams to navigate challenges and pursue shared objectives more effectively. Owner's Mindset: Owner's Mindset involves adopting a set of behaviors that reflect a sense of responsibility, accountability, strategic thinking, and a proactive approach to managing your domain. As an owner, you understand the business and your domain(s) deeply and solve for the right outcome for the domain(s) and the business. Requirements Bachelor's degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience Minimum 10 years of software engineering experience or comparable depth of experience A track record of setting and delivering multi-year technical strategy at enterprise scale, as an individual contributor rather than through a reporting line. Depth in distributed systems architecture, and in at least two of: agentic or LLM-based systems in production; large-scale cloud migration of transactional systems; modern data platform and lakehouse architecture; machine learning platform and model serving; high-traffic consumer or marketplace applications. Architecture ownership of agentic or LLM-based systems that reached production, including how tool and data access were governed, how the system was evaluated . click apply for full job details
Genesis10 is currently seeking a Senior AI Agentic Senior Technical Engineer for a 3+ month contract to hire opportunity with a Regional Financial Institution located in Columbus, OH; Akron, OH; Cleveland, OH; Cincinnati, OH; Minneapolis, MN; Dallas, TX; Detroit, MI; Ch Compensation: $107.00 - $117.00 per hour, W2, based on qualifications Position Overview: This role is responsible for building AI agents, developing API integrations, and implementing Pub/Sub messaging solutions. The ideal candidate understands the full agentic AI development lifecycle and has experience designing and developing AI solutions. Initially, the role focuses on building AI capabilities for the Commercial Services Loan Operations team, with the expectation that these solutions will eventually scale across the enterprise. This is a hands-on development role that involves close collaboration with cross-functional teams and ownership of projects to ensure continuity and successful delivery. Key Responsibilities: Design and implement production agent workflows using reference patterns: single-agent, supervised multi-agent, and tool-using agents Build tool integrations to enterprise services and banking systems (APIs, data products, document services) with strong error handling and audit logging Engineer RAG pipelines and retrieval behavior (chunking, embedding selection, re-ranking, context assembly) Implement agent memory and state management patterns that are compliant and operationally safe Create and maintain evaluation harnesses and regression suites for non-deterministic outputs Implement required guardrails (prompt injection defenses, tool restrictions, output filtering) and pass pre-deployment security gates Instrument agents for observability: decision traces, tool-call telemetry, retrieval diagnostics, token/cost metrics, and quality signals Ship via CI/CD with production readiness: feature flags, rollbacks, versioning, and runbooks Lead design and code reviews for agent components and mentor other engineers Debug complex failure modes and implement mitigations Primary Requirements: 7+ years in software engineering with 2+ years building LLM-enabled applications or agent systems in production Hands-on experience with at least one frontier model platform (Claude, GPT-4+, Gemini) including tool use and multi-turn workflow design Experience developing and integrating APIs Experience with end-to-end testing of agentic AI solutions Cloud engineering experience, including hands-on experience with Cloud Run Production delivery experience: CI/CD, containerization (Docker), and operational readiness (monitoring, logging, incident response) Java development experience Kubernetes experience Experience implementing and validating RAG systems (vector search, embeddings, retrieval quality) Ability to design for reliability and safety: failure mode thinking, graceful degradation, and clear human escalation paths Desired Skills: Azure or AWS experience Experience with Pub/Sub and event-driven architectures Experience in regulated financial services (SOX, GLBA, data classification, audit expectations) Experience with evaluation frameworks and model monitoring practices Experience building multi-agent orchestration and constraint systems Familiarity with secure software development (threat modeling, SAST/DAST, secrets management) Strong communication and collaboration skills Experience leading technical initiatives or engineering teams Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years Access to an experienced, caring recruiting team (more than 7 years of experience, on average) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all of our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
11/14/2026
Full time
Genesis10 is currently seeking a Senior AI Agentic Senior Technical Engineer for a 3+ month contract to hire opportunity with a Regional Financial Institution located in Columbus, OH; Akron, OH; Cleveland, OH; Cincinnati, OH; Minneapolis, MN; Dallas, TX; Detroit, MI; Ch Compensation: $107.00 - $117.00 per hour, W2, based on qualifications Position Overview: This role is responsible for building AI agents, developing API integrations, and implementing Pub/Sub messaging solutions. The ideal candidate understands the full agentic AI development lifecycle and has experience designing and developing AI solutions. Initially, the role focuses on building AI capabilities for the Commercial Services Loan Operations team, with the expectation that these solutions will eventually scale across the enterprise. This is a hands-on development role that involves close collaboration with cross-functional teams and ownership of projects to ensure continuity and successful delivery. Key Responsibilities: Design and implement production agent workflows using reference patterns: single-agent, supervised multi-agent, and tool-using agents Build tool integrations to enterprise services and banking systems (APIs, data products, document services) with strong error handling and audit logging Engineer RAG pipelines and retrieval behavior (chunking, embedding selection, re-ranking, context assembly) Implement agent memory and state management patterns that are compliant and operationally safe Create and maintain evaluation harnesses and regression suites for non-deterministic outputs Implement required guardrails (prompt injection defenses, tool restrictions, output filtering) and pass pre-deployment security gates Instrument agents for observability: decision traces, tool-call telemetry, retrieval diagnostics, token/cost metrics, and quality signals Ship via CI/CD with production readiness: feature flags, rollbacks, versioning, and runbooks Lead design and code reviews for agent components and mentor other engineers Debug complex failure modes and implement mitigations Primary Requirements: 7+ years in software engineering with 2+ years building LLM-enabled applications or agent systems in production Hands-on experience with at least one frontier model platform (Claude, GPT-4+, Gemini) including tool use and multi-turn workflow design Experience developing and integrating APIs Experience with end-to-end testing of agentic AI solutions Cloud engineering experience, including hands-on experience with Cloud Run Production delivery experience: CI/CD, containerization (Docker), and operational readiness (monitoring, logging, incident response) Java development experience Kubernetes experience Experience implementing and validating RAG systems (vector search, embeddings, retrieval quality) Ability to design for reliability and safety: failure mode thinking, graceful degradation, and clear human escalation paths Desired Skills: Azure or AWS experience Experience with Pub/Sub and event-driven architectures Experience in regulated financial services (SOX, GLBA, data classification, audit expectations) Experience with evaluation frameworks and model monitoring practices Experience building multi-agent orchestration and constraint systems Familiarity with secure software development (threat modeling, SAST/DAST, secrets management) Strong communication and collaboration skills Experience leading technical initiatives or engineering teams Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years Access to an experienced, caring recruiting team (more than 7 years of experience, on average) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all of our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Job Description Staff Full Stack Engineer AI Healthtech NYC Up to $240k + Equity The Company I'm working with a fast-growing Series B healthcare technology company in New York that is building software to solve some of the most complex problems in US healthcare. Their platform combines large-scale backend systems, data-heavy workflows and AI to help healthcare organisations improve accuracy, reduce waste and automate difficult processes. They're scaling their engineering team and looking for an experienced Staff Full Stack Engineer who can take genuine ownership of major technical challenges across the platform. This isn't an architecture-only position. They want someone who can set technical direction, influence engineering decisions and remain genuinely hands-on. The Role You'll play a key role in building and scaling the applications that sit at the centre of the company's AI-powered healthcare platform. This includes sophisticated React applications, complex operational workflows, backend services and data-intensive systems where performance, accuracy and reliability are critical. You'll have significant autonomy to make architectural decisions, improve engineering standards and influence how the wider team builds software. Key responsibilities: Own the architecture and delivery of complex full-stack systems, from frontend applications through to backend services. Build and scale production React and TypeScript applications, focusing on performance, component architecture, state management and user experience. Design robust APIs, backend services and relational data models supporting complex operational workflows. Make important system design decisions and establish engineering patterns across multiple teams. Work closely with product, design, backend and AI engineers to deliver intuitive applications powered by sophisticated backend systems. Champion modern engineering practices, including AI-assisted development, automated testing, observability and CI/CD. Mentor senior engineers, lead technical discussions and raise engineering standards while continuing to write production code. What They're Looking For 10+ years of software engineering experience , including genuine Staff-level technical ownership. Deep hands-on experience with React, TypeScript and modern JavaScript . Strong frontend architectural judgement, including reusable components, state management and application performance. Solid backend engineering experience with Python, Node.js or TypeScript , including APIs, databases and distributed systems. Experience architecting and delivering complex production applications end-to-end. Strong system design and cloud infrastructure knowledge, ideally AWS, Docker, Kubernetes and CI/CD. Proven experience mentoring engineers, influencing technical decisions and working effectively across teams. A strong product engineering background, ideally within high-growth technology companies or engineering-led startups. Someone who communicates clearly, makes thoughtful technical trade-offs and still enjoys getting into the code. Additional experience that would stand out: Building AI-powered applications, LLM integrations, agentic workflows or conversational interfaces. Healthcare, fintech or other regulated, data-intensive environments. B2B SaaS products involving complex operational workflows. GraphQL, PostgreSQL, Kafka or distributed data processing. Using AI coding tools such as Claude Code to improve engineering productivity. The Opportunity This is an opportunity to join a well-funded, growing engineering organisation at a point where individual engineers can still have a significant influence over the product and technical direction. You'll work on difficult engineering problems, help shape architecture across the stack and have the autonomy to build systems properly. It's particularly well suited to someone who wants the influence and ownership of a Staff Engineer while remaining closely involved in writing and shipping code. Location: New York City - 3 days per week onsite. Salary: Up to $240,000 base + equity. Level: Staff Engineer - Individual Contributor. If you're an experienced Staff Full Stack Engineer in New York who enjoys solving difficult problems, owning major systems and influencing how engineering teams build software, drop me a message. Happy to share more information about the company, the engineering team and the challenges they're tackling. If you're a Staff, Principal, Lead or exceptionally strong Senior Fullstack Engineer looking for serious technical ownership without moving away from coding, drop me a message.
11/14/2026
Full time
Job Description Staff Full Stack Engineer AI Healthtech NYC Up to $240k + Equity The Company I'm working with a fast-growing Series B healthcare technology company in New York that is building software to solve some of the most complex problems in US healthcare. Their platform combines large-scale backend systems, data-heavy workflows and AI to help healthcare organisations improve accuracy, reduce waste and automate difficult processes. They're scaling their engineering team and looking for an experienced Staff Full Stack Engineer who can take genuine ownership of major technical challenges across the platform. This isn't an architecture-only position. They want someone who can set technical direction, influence engineering decisions and remain genuinely hands-on. The Role You'll play a key role in building and scaling the applications that sit at the centre of the company's AI-powered healthcare platform. This includes sophisticated React applications, complex operational workflows, backend services and data-intensive systems where performance, accuracy and reliability are critical. You'll have significant autonomy to make architectural decisions, improve engineering standards and influence how the wider team builds software. Key responsibilities: Own the architecture and delivery of complex full-stack systems, from frontend applications through to backend services. Build and scale production React and TypeScript applications, focusing on performance, component architecture, state management and user experience. Design robust APIs, backend services and relational data models supporting complex operational workflows. Make important system design decisions and establish engineering patterns across multiple teams. Work closely with product, design, backend and AI engineers to deliver intuitive applications powered by sophisticated backend systems. Champion modern engineering practices, including AI-assisted development, automated testing, observability and CI/CD. Mentor senior engineers, lead technical discussions and raise engineering standards while continuing to write production code. What They're Looking For 10+ years of software engineering experience , including genuine Staff-level technical ownership. Deep hands-on experience with React, TypeScript and modern JavaScript . Strong frontend architectural judgement, including reusable components, state management and application performance. Solid backend engineering experience with Python, Node.js or TypeScript , including APIs, databases and distributed systems. Experience architecting and delivering complex production applications end-to-end. Strong system design and cloud infrastructure knowledge, ideally AWS, Docker, Kubernetes and CI/CD. Proven experience mentoring engineers, influencing technical decisions and working effectively across teams. A strong product engineering background, ideally within high-growth technology companies or engineering-led startups. Someone who communicates clearly, makes thoughtful technical trade-offs and still enjoys getting into the code. Additional experience that would stand out: Building AI-powered applications, LLM integrations, agentic workflows or conversational interfaces. Healthcare, fintech or other regulated, data-intensive environments. B2B SaaS products involving complex operational workflows. GraphQL, PostgreSQL, Kafka or distributed data processing. Using AI coding tools such as Claude Code to improve engineering productivity. The Opportunity This is an opportunity to join a well-funded, growing engineering organisation at a point where individual engineers can still have a significant influence over the product and technical direction. You'll work on difficult engineering problems, help shape architecture across the stack and have the autonomy to build systems properly. It's particularly well suited to someone who wants the influence and ownership of a Staff Engineer while remaining closely involved in writing and shipping code. Location: New York City - 3 days per week onsite. Salary: Up to $240,000 base + equity. Level: Staff Engineer - Individual Contributor. If you're an experienced Staff Full Stack Engineer in New York who enjoys solving difficult problems, owning major systems and influencing how engineering teams build software, drop me a message. Happy to share more information about the company, the engineering team and the challenges they're tackling. If you're a Staff, Principal, Lead or exceptionally strong Senior Fullstack Engineer looking for serious technical ownership without moving away from coding, drop me a message.
Job Description Senior Software Engineer Fort Meade, MD, US - Senior Level - Full-time Estimated Salary: The estimated salary range for this position is between $187,000 and $243,000 DOE About our client: Our client delivers high quality solutions and services to IC, DoD, Federal, and commercial customers. Their security, software, and systems engineers and architects work at the forefront of national challenges, solving some of the most complex problems in cyber analytics and data science. Our Client's Values Professionalism and a mission centric mindset are core to how they operate, shaping both their work and the way they conduct themselves. They take pride in fostering a culture of learning, growth, and excellence - for their employees, their partners, and the customers they serve. Description We are a cutting-edge technology company that is dedicated to developing innovative software solutions for our clients. We are currently seeking a talented and experienced Software Engineer to join our team. As a Software Engineer, you will be responsible for designing, developing, and implementing complex software capabilities for computer-based systems. Will work closely with other talented engineers to create software solutions that meet the needs of our clients. In this role, you will have the opportunity to work with modern tools and technologies, and you will be encouraged to stay up-to-date with the latest developments in the field. You will be part of a dynamic and collaborative team that is committed to delivering high-quality software solutions to our clients. If you are a self-motivated, creative, and detail-oriented software engineer who is passionate about developing innovative software solutions, we would love to hear from you. Requirements Essential Job Responsibilities Must have a strong working knowledge and experience developing Java based software capabilities. Should have an inquisitive nature, responsiveness, and excellent testing skills. Must also possess strong troubleshooting skills and the ability to work under pressure with multiple deadlines. Keep up-to-date with emerging trends and technologies in software development. Experience with Next-Gen Coding Agents: Proven track record of integrating advanced AI agents, specifically Claude Code or Google's Antigravity / Gemini agentic workflows, into your daily software engineering routine. Agentic Feature & Test Development: Experience using autonomous agents to handle multi-file feature implementations, complex codebase refactoring, and the automated generation of robust unit/integration tests. Context & Workflow Management: Ability to guide AI agents through complex, multi-repository application architectures, managing context efficiently and critically auditing agent-generated code for security, performance, and architectural alignment. Seamlessly transition between hands-on execution and team guidance, treating mentorship and team leadership as inherent components of senior-level impact. Will work in a fast-paced, small business environment with our talented team. Additional duties as assigned. Minimum Qualifications Clearance Requirement: Must obtain and maintain a U.S. Government Security Clearance, but not required on day one; U.S. Citizenship required. 9 years experience in Software Engineering, Modern Java Frameworks and Libraries (e.g. Spring, Guava) Bachelors in related field; 7 years relevant experience with Masters in related field; or High School Diploma or equivalent and 13 years relevant experience. Experience in designing enterprise APIs. Experience in RESTful web services. Experience in Microservices architecture. Experience in Object Oriented Programming (OOP) paradigms. Experience with the agile software lifecycle. Demonstrated experience serving as a tech lead, mentor, or manager for engineering teams. Has a proven ability to learn quickly and works well both independently as well as in a team setting. Experience with the Linux operating system. Experience with configuration management tools (e.g. Git, Nexus, Maven). Must be able to work in a hybrid environment, spending an average of 1-2 days per week on customer site in Fort Meade, MD. Will also be visits to our headquarters in Columbia, MD. Flexibility is essential to adapt to schedule changes as needed. Preferred Requirements Current Clearances: Active Secret clearance is a strong plus. Next-Gen Coding Agents: Proven use of AI tools (Claude Code, Gemini) in daily engineering workflows. Agentic Feature Delivery: Using autonomous agents for multi-file implementation, refactoring, and automated testing. Experience in cloud based technologies (AWS, Azure) Experience in distributed databases, NoSQL databases, full text-search engines (e.g. Elasticsearch, MongoDB, Solr) Scripting experience is a huge plus. Prior experience or familiarity with Data Lakes or Warehouses is a huge plus. Understanding of AGILE software development methodologies and use of standard software development tool suites. (e.g., JIRA, Confluence, Github Enterprise, etc.) Compensation Our client is building a team of like minded individuals who aren't afraid to work hard and support one another to achieve exceptional results. Fostering an environment where high calibre employees can shine means offering meaningful benefits and support both in the office and beyond. The benefits include health insurance, life insurance, disability insurance, financial and retirement plans, paid leave, professional development, tuition assistance, and dependent care. Salary varies based on location, education, skills, experience, as well as contract-specific affordability. The estimated salary range for this position is between $187,000 and $243,000. This estimate is one part of our client's overall compensation package.
11/14/2026
Full time
Job Description Senior Software Engineer Fort Meade, MD, US - Senior Level - Full-time Estimated Salary: The estimated salary range for this position is between $187,000 and $243,000 DOE About our client: Our client delivers high quality solutions and services to IC, DoD, Federal, and commercial customers. Their security, software, and systems engineers and architects work at the forefront of national challenges, solving some of the most complex problems in cyber analytics and data science. Our Client's Values Professionalism and a mission centric mindset are core to how they operate, shaping both their work and the way they conduct themselves. They take pride in fostering a culture of learning, growth, and excellence - for their employees, their partners, and the customers they serve. Description We are a cutting-edge technology company that is dedicated to developing innovative software solutions for our clients. We are currently seeking a talented and experienced Software Engineer to join our team. As a Software Engineer, you will be responsible for designing, developing, and implementing complex software capabilities for computer-based systems. Will work closely with other talented engineers to create software solutions that meet the needs of our clients. In this role, you will have the opportunity to work with modern tools and technologies, and you will be encouraged to stay up-to-date with the latest developments in the field. You will be part of a dynamic and collaborative team that is committed to delivering high-quality software solutions to our clients. If you are a self-motivated, creative, and detail-oriented software engineer who is passionate about developing innovative software solutions, we would love to hear from you. Requirements Essential Job Responsibilities Must have a strong working knowledge and experience developing Java based software capabilities. Should have an inquisitive nature, responsiveness, and excellent testing skills. Must also possess strong troubleshooting skills and the ability to work under pressure with multiple deadlines. Keep up-to-date with emerging trends and technologies in software development. Experience with Next-Gen Coding Agents: Proven track record of integrating advanced AI agents, specifically Claude Code or Google's Antigravity / Gemini agentic workflows, into your daily software engineering routine. Agentic Feature & Test Development: Experience using autonomous agents to handle multi-file feature implementations, complex codebase refactoring, and the automated generation of robust unit/integration tests. Context & Workflow Management: Ability to guide AI agents through complex, multi-repository application architectures, managing context efficiently and critically auditing agent-generated code for security, performance, and architectural alignment. Seamlessly transition between hands-on execution and team guidance, treating mentorship and team leadership as inherent components of senior-level impact. Will work in a fast-paced, small business environment with our talented team. Additional duties as assigned. Minimum Qualifications Clearance Requirement: Must obtain and maintain a U.S. Government Security Clearance, but not required on day one; U.S. Citizenship required. 9 years experience in Software Engineering, Modern Java Frameworks and Libraries (e.g. Spring, Guava) Bachelors in related field; 7 years relevant experience with Masters in related field; or High School Diploma or equivalent and 13 years relevant experience. Experience in designing enterprise APIs. Experience in RESTful web services. Experience in Microservices architecture. Experience in Object Oriented Programming (OOP) paradigms. Experience with the agile software lifecycle. Demonstrated experience serving as a tech lead, mentor, or manager for engineering teams. Has a proven ability to learn quickly and works well both independently as well as in a team setting. Experience with the Linux operating system. Experience with configuration management tools (e.g. Git, Nexus, Maven). Must be able to work in a hybrid environment, spending an average of 1-2 days per week on customer site in Fort Meade, MD. Will also be visits to our headquarters in Columbia, MD. Flexibility is essential to adapt to schedule changes as needed. Preferred Requirements Current Clearances: Active Secret clearance is a strong plus. Next-Gen Coding Agents: Proven use of AI tools (Claude Code, Gemini) in daily engineering workflows. Agentic Feature Delivery: Using autonomous agents for multi-file implementation, refactoring, and automated testing. Experience in cloud based technologies (AWS, Azure) Experience in distributed databases, NoSQL databases, full text-search engines (e.g. Elasticsearch, MongoDB, Solr) Scripting experience is a huge plus. Prior experience or familiarity with Data Lakes or Warehouses is a huge plus. Understanding of AGILE software development methodologies and use of standard software development tool suites. (e.g., JIRA, Confluence, Github Enterprise, etc.) Compensation Our client is building a team of like minded individuals who aren't afraid to work hard and support one another to achieve exceptional results. Fostering an environment where high calibre employees can shine means offering meaningful benefits and support both in the office and beyond. The benefits include health insurance, life insurance, disability insurance, financial and retirement plans, paid leave, professional development, tuition assistance, and dependent care. Salary varies based on location, education, skills, experience, as well as contract-specific affordability. The estimated salary range for this position is between $187,000 and $243,000. This estimate is one part of our client's overall compensation package.
Pay Range: $60.00hr - $65.00hr Job Overview: As an Engineer, the candidate is responsible for building, designing, and deploying modern web applications. The candidate will leverage technical skills to architect scalable and robust solutions, tackle dependencies, and shape the team's technical strategy. Our client is looking for a Senior AI Engineer with Java Full Stack Experience to join a learner-centered team committed to delivering a next-generation transformative AI-powered learning infrastructure. In this role, the candidate will influence the future of learning experiences by developing integrated and scalable solutions from the ground up within a supportive and collaborative environment. Responsibilities: Collaborate closely with subject matter experts to understand challenges and translate them into effective solution designs, partnering with Product, UX, and other engineering teams. Drive AI efforts including Gemini integrations, ML model fine-tuning, evaluation, and performance optimization to create user-facing solutions that are both scalable and high-performant. Drive cross-functional collaboration to prototype web solutions, gather feedback, and iteratively refine requirements. Develop, test, and monitor robust, scalable, and reliable web solutions that meet business needs. Leverage cloud solutions and tools to create seamlessly integrated, reusable, and extensible systems. Write and review technical documents (product, technical design, developer documentation) and code in Angular, TypeScript, Java, Kotlin, Python, or SQL. Build the organization's agentic future by implementing Gemini integrations, assisting with ML model fine-tuning, and executing AI performance evaluations to help develop intelligent, user-facing learning solutions. Design, build, and deploy full-stack web solutions that are reliable, scalable, and high-performant, using advanced technologies to build AI-powered learning flows. Minimum qualifications: Bachelor's degree or equivalent practical experience. 10+ years of experience with Software Development in Java Fullstack (Java, Angular). 2+ years of experience in AI Technologies. Generative AI & LLMs: Demonstrated track record of deploying Gemini models in production using Vertex AI and the Agent Development Kit (ADK). RAG Architecture: Proven expertise in designing RAG systems. Backend & Cloud Infrastructure: Strong proficiency in Python (FastAPI), Cloud Run, and large-scale data retrieval strategies. Data Structures & Storage: Experience with relational database architecture and enterprise data schema management. Experience working with one or more of the following: web or mobile application development, Unix/Linux environments, distributed and parallel systems, machine learning, information retrieval, natural language processing, networking, developing software systems, or security. Strong verbal and written communication skills with stakeholder management capabilities. Preferred qualifications: Demonstrated experience with service architecture, domain-driven design, and the development of scalable, distributed services. Demonstrated experience in the end-to-end design, scaling, and performance tuning of AI-integrated web applications within dynamic environments. Demonstrated experience running Kanban boards and sprints while forecasting effort for complex engineering projects. Demonstrated experience with ADK, MCP, and integrating Gemini AI APIs into production web applications. Demonstrated experience with ML model fine-tuning, evaluation, and performance optimization for user-facing systems. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
11/14/2026
Full time
Pay Range: $60.00hr - $65.00hr Job Overview: As an Engineer, the candidate is responsible for building, designing, and deploying modern web applications. The candidate will leverage technical skills to architect scalable and robust solutions, tackle dependencies, and shape the team's technical strategy. Our client is looking for a Senior AI Engineer with Java Full Stack Experience to join a learner-centered team committed to delivering a next-generation transformative AI-powered learning infrastructure. In this role, the candidate will influence the future of learning experiences by developing integrated and scalable solutions from the ground up within a supportive and collaborative environment. Responsibilities: Collaborate closely with subject matter experts to understand challenges and translate them into effective solution designs, partnering with Product, UX, and other engineering teams. Drive AI efforts including Gemini integrations, ML model fine-tuning, evaluation, and performance optimization to create user-facing solutions that are both scalable and high-performant. Drive cross-functional collaboration to prototype web solutions, gather feedback, and iteratively refine requirements. Develop, test, and monitor robust, scalable, and reliable web solutions that meet business needs. Leverage cloud solutions and tools to create seamlessly integrated, reusable, and extensible systems. Write and review technical documents (product, technical design, developer documentation) and code in Angular, TypeScript, Java, Kotlin, Python, or SQL. Build the organization's agentic future by implementing Gemini integrations, assisting with ML model fine-tuning, and executing AI performance evaluations to help develop intelligent, user-facing learning solutions. Design, build, and deploy full-stack web solutions that are reliable, scalable, and high-performant, using advanced technologies to build AI-powered learning flows. Minimum qualifications: Bachelor's degree or equivalent practical experience. 10+ years of experience with Software Development in Java Fullstack (Java, Angular). 2+ years of experience in AI Technologies. Generative AI & LLMs: Demonstrated track record of deploying Gemini models in production using Vertex AI and the Agent Development Kit (ADK). RAG Architecture: Proven expertise in designing RAG systems. Backend & Cloud Infrastructure: Strong proficiency in Python (FastAPI), Cloud Run, and large-scale data retrieval strategies. Data Structures & Storage: Experience with relational database architecture and enterprise data schema management. Experience working with one or more of the following: web or mobile application development, Unix/Linux environments, distributed and parallel systems, machine learning, information retrieval, natural language processing, networking, developing software systems, or security. Strong verbal and written communication skills with stakeholder management capabilities. Preferred qualifications: Demonstrated experience with service architecture, domain-driven design, and the development of scalable, distributed services. Demonstrated experience in the end-to-end design, scaling, and performance tuning of AI-integrated web applications within dynamic environments. Demonstrated experience running Kanban boards and sprints while forecasting effort for complex engineering projects. Demonstrated experience with ADK, MCP, and integrating Gemini AI APIs into production web applications. Demonstrated experience with ML model fine-tuning, evaluation, and performance optimization for user-facing systems. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Job Description Job Title: Cloud Solutions Architect / Cloud Engineer /Application Architect- AI Agentic, Integration & Architecture Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Duration: Long Term Contract Certification/Experience: Cloud certification and additional relevant certification Position Summary We are seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. 1. AI Agentic Architecture -Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. - Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). - Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture - Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. - Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE - Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. - Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. - Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration - Guide application modernization and cloud design on Azure, AWS, and hybrid environments. - Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and security requirements. - Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Qualifications 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication
11/14/2026
Full time
Job Description Job Title: Cloud Solutions Architect / Cloud Engineer /Application Architect- AI Agentic, Integration & Architecture Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Duration: Long Term Contract Certification/Experience: Cloud certification and additional relevant certification Position Summary We are seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. 1. AI Agentic Architecture -Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. - Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). - Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture - Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. - Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE - Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. - Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. - Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration - Guide application modernization and cloud design on Azure, AWS, and hybrid environments. - Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and security requirements. - Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Qualifications 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication
Job Description End Client: Metropolitan Transportation Authority (MTA) Job Title: Senior AI & Cloud Solutions Architect Duration: 12 months + Extension Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Number of Hours: 37.5 Hours a week Interview Type: Webcam or In-Person Ceipal ID: MTA_AI122_MA Job Code: 6122-1 Scope of Project: The MTA is seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. Responsibilities: 1. AI Agentic Architecture Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration Guide application modernization and cloud design on Azure, AWS, and hybrid environments. Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and MTA security requirements. Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Required/Preferred Skills: 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication. Cloud certification and additional relevant certification preferred. Expertise in agentic AI architecture, multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Experience with enterprise systems and APIs, MCP, and event-driven triggers. Knowledge of API-led, event-driven, and messaging integration patterns, API lifecycle, and gateway strategy. Experience with legacy, SaaS, and cloud-native integration. Experience developing application, integration, API, and AI architecture standards and reference architectures. Experience establishing and operating an Architecture Center of Excellence (COE), including governance forums, design reviews, training, and playbooks. Knowledge of Azure, AWS, hybrid cloud environments, NIST AI RMF, CIS, ISO 27001, and enterprise security requirements. V Group Inc. is a NJ-based IT Services and Products Company with its business strategically categorized in various Business Units including Public Sector, Enterprise Solutions, Professional Services, Ecommerce, Projects, and Products. Within Public Sector business unit, we cater IT Professional Services to Federal, State and Local. We have multiple awards/ contracts with 30+ states, including but not limited to NY, CA, FL, GA, MD, MI, NC, OH, OR, CO, CT, TN, PA, TX, VA, NM, VT, and WA. If you are considering applying for a position with V Group, or in partnering with us on a position, please feel free to contact me for any questions you may have regarding our services and the advantages we can offer you as a consultant. Please share my contact information with others working in Information Technology. Website: LinkedIn: -group/ Facebook: Twitter:
11/14/2026
Full time
Job Description End Client: Metropolitan Transportation Authority (MTA) Job Title: Senior AI & Cloud Solutions Architect Duration: 12 months + Extension Location: New York, NY (Hybrid - 3 Days Onsite, 2 Days Remote) Number of Hours: 37.5 Hours a week Interview Type: Webcam or In-Person Ceipal ID: MTA_AI122_MA Job Code: 6122-1 Scope of Project: The MTA is seeking a Senior Cloud Solutions Architect / Cloud Engineer/Application Architect with deep expertise in AI agentic architecture, enterprise integration, and architecture standards. This hands-on role designs agent-based and AI-enabled solutions, defines integration patterns, publishes application architecture standards, and helps establish an Architecture Center of Excellence (COE). The architect will work in Azure, AWS, and hybrid environments. Responsibilities: 1. AI Agentic Architecture Design reference architectures for agentic AI: multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Define secure patterns for integrating agents with enterprise systems and APIs (e.g., MCP, event-driven triggers). Establish guardrails for agent identity, access, auditability, observability, evaluation, and cost. 2. Integration Architecture Design and govern API-led, event-driven, and messaging integration patterns, including API lifecycle and gateway strategy. Define integration patterns for legacy, SaaS, and cloud-native systems. 3. Standards & Architecture COE Develop, publish, and maintain application, integration, API, and AI architecture standards and reference architectures. Help establish and operate the COE: charter, governance forums, design reviews, training, and playbooks. Define COE and standards-adoption metrics in coordination with AI IT adoption tracking. 4. Modernization, Security & Collaboration Guide application modernization and cloud design on Azure, AWS, and hybrid environments. Align designs with NIST (incl. AI RMF), CIS, ISO 27001, and MTA security requirements. Partner with product, engineering, DevOps, and Cybersecurity teams; communicate clearly to business and technical stakeholders. Required/Preferred Skills: 10+ years of application/enterprise architecture experience, including cloud-native design on Azure and/or AWS. Experience delivering AI/LLM or agentic solutions in an enterprise. Experience authoring standards and operating an architecture COE or review board. Strong integration/API expertise and executive-level communication. Cloud certification and additional relevant certification preferred. Expertise in agentic AI architecture, multi-agent orchestration, tool calling, RAG, and human-in-the-loop controls. Experience with enterprise systems and APIs, MCP, and event-driven triggers. Knowledge of API-led, event-driven, and messaging integration patterns, API lifecycle, and gateway strategy. Experience with legacy, SaaS, and cloud-native integration. Experience developing application, integration, API, and AI architecture standards and reference architectures. Experience establishing and operating an Architecture Center of Excellence (COE), including governance forums, design reviews, training, and playbooks. Knowledge of Azure, AWS, hybrid cloud environments, NIST AI RMF, CIS, ISO 27001, and enterprise security requirements. V Group Inc. is a NJ-based IT Services and Products Company with its business strategically categorized in various Business Units including Public Sector, Enterprise Solutions, Professional Services, Ecommerce, Projects, and Products. Within Public Sector business unit, we cater IT Professional Services to Federal, State and Local. We have multiple awards/ contracts with 30+ states, including but not limited to NY, CA, FL, GA, MD, MI, NC, OH, OR, CO, CT, TN, PA, TX, VA, NM, VT, and WA. If you are considering applying for a position with V Group, or in partnering with us on a position, please feel free to contact me for any questions you may have regarding our services and the advantages we can offer you as a consultant. Please share my contact information with others working in Information Technology. Website: LinkedIn: -group/ Facebook: Twitter:
Job Description Intellibus Consulting is a boutique engineering and AI transformation firm that builds mission-critical platforms for global financial institutions. We operate at the intersection of engineering excellence, business outcomes, and executive-level delivery. At Intellibus, our leaders are hands-on builders who understand technology deeply, engage confidently with senior executives, and take ownership of client success. We believe successful technology transformation requires leaders who can connect business strategy, architecture, engineering, and execution Job Description We are looking for exceptional Forward Deployed Engineers with deep hands-on software engineering expertise, particularly in Java, backend engineering, full-stack development, microservices, and distributed systems. This is a highly technical, client-facing engineering role that requires someone who can move seamlessly between architecture, software development, solution delivery, and executive-level client engagement. You will work directly with client engineering teams, technology leaders, and business stakeholders to understand complex challenges, design technical solutions, and lead the development and implementation of enterprise-grade platforms. Beyond engineering delivery, you will play an important role in expanding strategic client relationships by identifying technology opportunities, recommending solutions, demonstrating technical capabilities, and helping grow existing accounts. We are specifically looking for engineers who have worked in technology consulting or professional services environments and are comfortable taking ownership of both technical delivery and client relationships. Key Responsibilities Hands-on Software Engineering & Architecture Design, develop, and deliver scalable enterprise applications using Java and modern software engineering technologies. Demonstrate deep hands-on expertise in Java, Spring Boot, Spring Framework, REST APIs, and backend application development. Build complex microservices-based architectures, distributed systems, and event-driven applications. Develop full-stack solutions with strong backend capabilities and practical frontend development experience. Work across the entire software development lifecycle, from architecture and design through coding, testing, deployment, and production support. Lead technical implementation while remaining actively involved in writing and reviewing code. Develop reusable components, APIs, integrations, and enterprise application frameworks. Troubleshoot performance bottlenecks, scalability challenges, concurrency issues, and complex production defects. Backend, Frontend & Full-Stack Development Build backend services using Java, Spring Boot, Hibernate, JPA, and related technologies. Design and implement RESTful APIs, microservices, and enterprise integrations. Develop frontend applications using React, JavaScript, TypeScript, HTML, and CSS. Integrate frontend applications with backend services and enterprise platforms. Work with relational and NoSQL databases, including PostgreSQL, Oracle, MongoDB, or similar technologies. Implement authentication, authorization, security, and API integration patterns. Ensure application performance, maintainability, reliability, and scalability. Microservices & Cloud-Native Engineering Design and implement microservices architectures and distributed application platforms. Work with messaging and event-streaming technologies such as Apache Kafka. Build asynchronous processing, event-driven integrations, and resilient distributed services. Apply design patterns for service discovery, fault tolerance, circuit breakers, and distributed transactions. Deploy and operate applications on AWS, Azure, or GCP. Work with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation. Apply observability practices using logging, monitoring, tracing, and performance management tools. Understand cloud-native architecture, scalability, availability, and system reliability. AI & Agentic Engineering Explore and implement AI-powered enterprise applications and intelligent workflows. Integrate LLMs and AI capabilities into existing enterprise applications and platforms. Develop AI agents, tool-calling workflows, and agent orchestration capabilities. Work with retrieval-augmented generation (RAG), vector databases, and enterprise data integrations. Identify opportunities to apply AI and automation to solve client business and technology challenges. Build practical prototypes and take successful AI solutions through production implementation. Client Consulting & Strategic Account Growth Work directly with client CTOs, CIOs, engineering leaders, architects, and business stakeholders. Understand client technology environments, business priorities, and strategic challenges. Translate business problems into technical solutions and actionable engineering roadmaps. Lead technical discovery sessions, architecture discussions, solution demonstrations, and client workshops. Identify opportunities for platform modernization, application development, cloud transformation, and AI adoption. Help expand existing client engagements by identifying new projects, engineering opportunities, and areas where Intellibus can add value. Build trusted relationships with client stakeholders and contribute to long-term account growth. Prepare technical proposals, solution presentations, architecture diagrams, and executive-level materials. Collaborate with leadership and account teams to shape new opportunities and support business development. Required Technical Expertise Java & Backend Engineering Extensive hands-on experience with Java and Spring Boot. Strong understanding of OOP, multithreading, concurrency, collections, JVM fundamentals, and performance optimization. Experience with REST APIs, Hibernate, JPA, and enterprise application development. Strong knowledge of backend architecture and enterprise integration patterns. Full-Stack Development Experience building frontend applications using React, JavaScript, and TypeScript. Ability to independently work across backend and frontend components. Strong understanding of API integration and application architecture. Microservices & Distributed Systems Deep experience designing and implementing microservices architectures. Strong knowledge of Kafka, event-driven systems, messaging, and distributed computing. Understanding of scalability, resiliency, fault tolerance, and high-availability architecture. Cloud & DevOps Experience with AWS, Azure, or GCP. Hands-on experience with Docker, Kubernetes, CI/CD, and cloud-native deployments. Familiarity with Terraform or other infrastructure-as-code tools is preferred. AI & Modern Engineering Exposure to LLM integrations, generative AI, AI agents, and agentic workflows. Experience integrating AI capabilities into enterprise software is highly desirable. Required Consulting & Client Engagement Experience Previous experience working for a technology consulting firm, systems integrator, or professional services organization is mandatory. Demonstrated experience delivering technology solutions for external enterprise clients. Ability to manage multiple technical stakeholders and work across different client environments. Strong executive communication and presentation skills. Ability to identify additional technology opportunities and contribute to account expansion. Comfortable operating in fast-paced consulting environments where priorities and client requirements can evolve. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience. Significant professional software engineering experience, ideally 8+ years. Extensive hands-on Java and backend engineering experience. Proven experience building enterprise-grade microservices and distributed systems. Full-stack development experience with modern frontend frameworks. Previous consulting or professional services experience is mandatory. Experience working in financial services, banking, fintech, or other regulated industries is strongly preferred. What Success Looks Like You can independently design, code, and deliver complex enterprise applications. You bring deep technical expertise in Java, backend engineering, full-stack development, and microservices. You can engage with client engineering teams and senior executives with equal confidence. You identify opportunities to solve broader client challenges beyond the immediate assignment. You help strengthen client relationships and contribute to expanding strategic accounts. You take ownership of solutions from initial discovery through architecture, implementation, and production deployment. Who Should Apply? We are looking for engineers who are not limited to writing code against predefined requirements. . click apply for full job details
11/14/2026
Full time
Job Description Intellibus Consulting is a boutique engineering and AI transformation firm that builds mission-critical platforms for global financial institutions. We operate at the intersection of engineering excellence, business outcomes, and executive-level delivery. At Intellibus, our leaders are hands-on builders who understand technology deeply, engage confidently with senior executives, and take ownership of client success. We believe successful technology transformation requires leaders who can connect business strategy, architecture, engineering, and execution Job Description We are looking for exceptional Forward Deployed Engineers with deep hands-on software engineering expertise, particularly in Java, backend engineering, full-stack development, microservices, and distributed systems. This is a highly technical, client-facing engineering role that requires someone who can move seamlessly between architecture, software development, solution delivery, and executive-level client engagement. You will work directly with client engineering teams, technology leaders, and business stakeholders to understand complex challenges, design technical solutions, and lead the development and implementation of enterprise-grade platforms. Beyond engineering delivery, you will play an important role in expanding strategic client relationships by identifying technology opportunities, recommending solutions, demonstrating technical capabilities, and helping grow existing accounts. We are specifically looking for engineers who have worked in technology consulting or professional services environments and are comfortable taking ownership of both technical delivery and client relationships. Key Responsibilities Hands-on Software Engineering & Architecture Design, develop, and deliver scalable enterprise applications using Java and modern software engineering technologies. Demonstrate deep hands-on expertise in Java, Spring Boot, Spring Framework, REST APIs, and backend application development. Build complex microservices-based architectures, distributed systems, and event-driven applications. Develop full-stack solutions with strong backend capabilities and practical frontend development experience. Work across the entire software development lifecycle, from architecture and design through coding, testing, deployment, and production support. Lead technical implementation while remaining actively involved in writing and reviewing code. Develop reusable components, APIs, integrations, and enterprise application frameworks. Troubleshoot performance bottlenecks, scalability challenges, concurrency issues, and complex production defects. Backend, Frontend & Full-Stack Development Build backend services using Java, Spring Boot, Hibernate, JPA, and related technologies. Design and implement RESTful APIs, microservices, and enterprise integrations. Develop frontend applications using React, JavaScript, TypeScript, HTML, and CSS. Integrate frontend applications with backend services and enterprise platforms. Work with relational and NoSQL databases, including PostgreSQL, Oracle, MongoDB, or similar technologies. Implement authentication, authorization, security, and API integration patterns. Ensure application performance, maintainability, reliability, and scalability. Microservices & Cloud-Native Engineering Design and implement microservices architectures and distributed application platforms. Work with messaging and event-streaming technologies such as Apache Kafka. Build asynchronous processing, event-driven integrations, and resilient distributed services. Apply design patterns for service discovery, fault tolerance, circuit breakers, and distributed transactions. Deploy and operate applications on AWS, Azure, or GCP. Work with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation. Apply observability practices using logging, monitoring, tracing, and performance management tools. Understand cloud-native architecture, scalability, availability, and system reliability. AI & Agentic Engineering Explore and implement AI-powered enterprise applications and intelligent workflows. Integrate LLMs and AI capabilities into existing enterprise applications and platforms. Develop AI agents, tool-calling workflows, and agent orchestration capabilities. Work with retrieval-augmented generation (RAG), vector databases, and enterprise data integrations. Identify opportunities to apply AI and automation to solve client business and technology challenges. Build practical prototypes and take successful AI solutions through production implementation. Client Consulting & Strategic Account Growth Work directly with client CTOs, CIOs, engineering leaders, architects, and business stakeholders. Understand client technology environments, business priorities, and strategic challenges. Translate business problems into technical solutions and actionable engineering roadmaps. Lead technical discovery sessions, architecture discussions, solution demonstrations, and client workshops. Identify opportunities for platform modernization, application development, cloud transformation, and AI adoption. Help expand existing client engagements by identifying new projects, engineering opportunities, and areas where Intellibus can add value. Build trusted relationships with client stakeholders and contribute to long-term account growth. Prepare technical proposals, solution presentations, architecture diagrams, and executive-level materials. Collaborate with leadership and account teams to shape new opportunities and support business development. Required Technical Expertise Java & Backend Engineering Extensive hands-on experience with Java and Spring Boot. Strong understanding of OOP, multithreading, concurrency, collections, JVM fundamentals, and performance optimization. Experience with REST APIs, Hibernate, JPA, and enterprise application development. Strong knowledge of backend architecture and enterprise integration patterns. Full-Stack Development Experience building frontend applications using React, JavaScript, and TypeScript. Ability to independently work across backend and frontend components. Strong understanding of API integration and application architecture. Microservices & Distributed Systems Deep experience designing and implementing microservices architectures. Strong knowledge of Kafka, event-driven systems, messaging, and distributed computing. Understanding of scalability, resiliency, fault tolerance, and high-availability architecture. Cloud & DevOps Experience with AWS, Azure, or GCP. Hands-on experience with Docker, Kubernetes, CI/CD, and cloud-native deployments. Familiarity with Terraform or other infrastructure-as-code tools is preferred. AI & Modern Engineering Exposure to LLM integrations, generative AI, AI agents, and agentic workflows. Experience integrating AI capabilities into enterprise software is highly desirable. Required Consulting & Client Engagement Experience Previous experience working for a technology consulting firm, systems integrator, or professional services organization is mandatory. Demonstrated experience delivering technology solutions for external enterprise clients. Ability to manage multiple technical stakeholders and work across different client environments. Strong executive communication and presentation skills. Ability to identify additional technology opportunities and contribute to account expansion. Comfortable operating in fast-paced consulting environments where priorities and client requirements can evolve. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience. Significant professional software engineering experience, ideally 8+ years. Extensive hands-on Java and backend engineering experience. Proven experience building enterprise-grade microservices and distributed systems. Full-stack development experience with modern frontend frameworks. Previous consulting or professional services experience is mandatory. Experience working in financial services, banking, fintech, or other regulated industries is strongly preferred. What Success Looks Like You can independently design, code, and deliver complex enterprise applications. You bring deep technical expertise in Java, backend engineering, full-stack development, and microservices. You can engage with client engineering teams and senior executives with equal confidence. You identify opportunities to solve broader client challenges beyond the immediate assignment. You help strengthen client relationships and contribute to expanding strategic accounts. You take ownership of solutions from initial discovery through architecture, implementation, and production deployment. Who Should Apply? We are looking for engineers who are not limited to writing code against predefined requirements. . click apply for full job details
Job Description Job Description Genesis10 is currently seeking a Senior AI Engineer (Generative AI & Agentic Systems) for a contract position with a Global Financial Institution located in Pennington, NJ. This is a 12+ month contract opportunity. We are seeking an Advanced Python Engineer with specialized expertise in Generative AI orchestration, multi-agent workflows, and Retrieval-Augmented Generation (RAG) systems. In this role, you will design, build, and scale production-grade LLM applications, leveraging modern agentic frameworks to power intelligent enterprise solutions. Key Responsibilities: Architect and scale advanced Retrieval-Augmented Generation (RAG) pipelines, including custom chunking, hybrid search, embedding optimization, and reranking mechanisms Build complex, stateful multi-agent systems and autonomous workflows using frameworks such as LangGraph and Deepagents Orchestrate and monitor using LangChain for robust LLM integration and LangSmith for tracing, evaluation, debugging, and performance monitoring of production LLM pipelines Write clean, modular, highly efficient, and maintainable Python code adhering to modern standards (asynchronous programming, strict typing, and robust error handling) Connect LLM agents and workflows with external data sources, enterprise APIs, vector databases, and developer tooling Optimize token usage, latency, and operational costs across LLM-driven applications without compromising response quality or accuracy Requirements: Advanced, production-level proficiency in Python (asyncio, design patterns, profiling, and testing) Demonstrated hands-on production experience with one or more of the following: LangChain, LangGraph, LangSmith, Deepagents Deep working knowledge of RAG pipelines, prompt engineering strategies, and integration with vector databases (e.g., Pinecone, Weaviate, Milvus, Qdrant, or pgvector) Familiarity with major LLM providers (OpenAI, Anthropic, open-source models via Hugging Face/Ollama) and function-calling / tool-use architectures Experience with Git, CI/CD pipelines, containerization (Docker), and cloud environments (AWS, GCP, or Azure) Pay range: $55.06 - $63.06 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
11/13/2026
Full time
Job Description Job Description Genesis10 is currently seeking a Senior AI Engineer (Generative AI & Agentic Systems) for a contract position with a Global Financial Institution located in Pennington, NJ. This is a 12+ month contract opportunity. We are seeking an Advanced Python Engineer with specialized expertise in Generative AI orchestration, multi-agent workflows, and Retrieval-Augmented Generation (RAG) systems. In this role, you will design, build, and scale production-grade LLM applications, leveraging modern agentic frameworks to power intelligent enterprise solutions. Key Responsibilities: Architect and scale advanced Retrieval-Augmented Generation (RAG) pipelines, including custom chunking, hybrid search, embedding optimization, and reranking mechanisms Build complex, stateful multi-agent systems and autonomous workflows using frameworks such as LangGraph and Deepagents Orchestrate and monitor using LangChain for robust LLM integration and LangSmith for tracing, evaluation, debugging, and performance monitoring of production LLM pipelines Write clean, modular, highly efficient, and maintainable Python code adhering to modern standards (asynchronous programming, strict typing, and robust error handling) Connect LLM agents and workflows with external data sources, enterprise APIs, vector databases, and developer tooling Optimize token usage, latency, and operational costs across LLM-driven applications without compromising response quality or accuracy Requirements: Advanced, production-level proficiency in Python (asyncio, design patterns, profiling, and testing) Demonstrated hands-on production experience with one or more of the following: LangChain, LangGraph, LangSmith, Deepagents Deep working knowledge of RAG pipelines, prompt engineering strategies, and integration with vector databases (e.g., Pinecone, Weaviate, Milvus, Qdrant, or pgvector) Familiarity with major LLM providers (OpenAI, Anthropic, open-source models via Hugging Face/Ollama) and function-calling / tool-use architectures Experience with Git, CI/CD pipelines, containerization (Docker), and cloud environments (AWS, GCP, or Azure) Pay range: $55.06 - $63.06 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
This job is with Colt Technology Services, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Colt provides network, voice and data centre services to thousands of businesses around the world, allowing them to focus on delivering their business goals instead of the underlying infrastructure. Summary Job title : Senior AI Engineer Reports to : VP of AI Technology and Architecture Job location : Must have ability to be onsite in Boulder, CO office for 2-3 days a week About Colt and the AI Practice Colt Technology Services is a global digital infrastructure company, operating one of the world's largest fiber networks across Europe and Asia. We are building a Boulder-based AI team as the engineering center of our AI Practice. The team is responsible for how AI is adopted, governed, and scaled across Colt. The AI Practice operates across several parallel workstreams, including use case delivery, AI WAN, and private AI. The Boulder team is where we build, test, and validate before we scale. Why we need this role This is a build role. You will take AI use cases from a business problem to something running in production and being used every day: retrieval and search over Colt's own data, agents that carry out multi-step work, and AI built into the systems Colt's teams already rely on. We are looking for a strong software engineer first. If you have spent eight to ten years building and running production systems and even if you have not yet shipped an LLM-based product, we want to hear from. The platform, the tooling, and the model access are already in place, and a staff-level AI engineer on the team will pair with you directly on the AI side of the work. The AI-specific skills you can bring to the table is a plus but is also learnable. The engineering experience and judgement that comes from having owned real systems in production is not, and that is the part we are hiring for. What we do expect is that you have already got hands on with AI, whether at work or as a side project for yourself. You will be working directly with the Colt teams taking requirements from them. The team is small by design, the problems are real, and what you build in your first year sets the pattern for how Colt builds AI. What you will do Build AI Use Cases Design and build AI applications end to end: data access, retrieval, model calls, orchestration, and the interfaces people use Work with large language models through APIs and self-hosted inference, covering prompting, tool use, retrieval, and multi-step agent workflows Build evaluation harnesses that show whether a use case is good enough to ship, and keep owning them after it ships Integrate AI into Colt's existing systems and data, within the constraints of a live enterprise environment Work Directly With the Business Work with the Colt teams, who will be your customers, and who will use what you build, across network operations, service delivery, finance, and others Turn a loosely described business problem into a scoped, buildable design Show working software early and often, and change direction when the first answer turns out to be wrong Be straight with stakeholders about what AI is not the right tool for Take It to Production and Keep It There Move your own work from prototype to production-grade: tested, instrumented, documented, and supportable Monitor accuracy, latency, and cost in production, and act when they drift Work with platform engineers on deployment, and hand over cleanly to production operations Contribute reusable patterns, components, and internal libraries so the next use case is faster than the last What we're looking for Engineering Experience: 8-10+ years building production software. You have owned systems end to end: designed them, shipped them, operated them, and been on the hook when they broke. Languages: Strong in Python, or strong in another language such as Java, Go, C#, or TypeScript and ready to work primarily in Python. Production Systems: APIs and service integration, working with real data at scale, testing, CI/CD, and debugging things that are already live in front of users. Cloud: Comfortable in any major cloud. We build primarily on Google Cloud; equivalent AWS or Azure experience is ok to start. Working Style: Comfortable with ambiguity and with direct contact with non-technical stakeholders. You ask what the problem is before deciding what to build. Hands-On with AI: You have already built something with it under your own steam. A side project, a prototype at work, an internal tool, a serious evaluation you ran, or agentic coding tools you use daily and have opinions about. It does not need to have shipped, been finished, or worked. We want to hear what you tried, what broke, and what you concluded. Helpful, Not Required: Any of this at enterprise scale: production RAG over messy real-world data, agent frameworks, evaluation tooling, Vertex AI, Kubernetes, Terraform. Useful if you have it, and teachable if you do not. HOW YOU WILL RAMP You pair with a staff-level AI engineer from your first week, on a live use case rather than a training exercise The AI platform is already running: model gateway, evaluation tooling, deployment pipelines, and sandbox, development, and production environments We expect you to put something small into real use inside your first 90 days, and to lead a use case end to end within six months WHEN WE TALK Come ready to walk us through something you have built with AI, however small or unfinished. We would rather see a rough prototype you can explain in depth than a polished project you cannot. Expect us to ask where it fell short, what you would do differently, and how you decided whether it was any good. How you evaluated it matters more to us than what you shipped. If you have not used AI tools in your own engineering work, this will be a difficult conversation. That is the one gap we are not set up to close for you. What we offer you: Looking to make a mark? At Colt, you'll make a difference. Because around here, we empower people. We don't tell you what to do. Instead, we employ people we trust, who come together across the globe to create intelligent solutions. Our global teams are full of ambitious, driven people, all working together towards one shared purpose: to put the power of the digital universe in the hands of our customers wherever, whenever and however they want. We give our people the opportunity to inspire and lead teams, and work on projects that connect people, cities, businesses, and ideas. We want you to help us change the world, for the better. Diversity and inclusion Inclusion and valuing diversity of thought and experience are at the heart of our culture here at Colt. From day one, you'll be encouraged to be yourself because we believe that's what helps our people to thrive. We welcome people with diverse backgrounds and experiences, regardless of their gender identity or expression, sexual orientation, race, religion, disability, neurodiversity, age, marital status, pregnancy status, or place of birth. Most recently we have: Signed the UN Women Empowerment Principles which guide our Gender Action Plan Trained 60 (and growing) Colties to be Mental Health First Aiders Please speak with a member of our recruitment team if you require adjustments to our recruitment process to support you. For more information about our Inclusion and Diversity agenda, visit our DEI pages . Benefits Our benefits support you through all parts of life, for both physical and mental health. Flexible working hours and the option to work from home. Extensive induction program with experienced mentors and buddies. Opportunities for further development and educational opportunities. Global Family Leave Policy. Employee Assistance Program. Internal inclusion & diversity employee networks. A global network When you join Colt you become part of our global network. We are proud of our colleagues and the stories and experience they bring - take a look at 'Our People' site including our Empowered Women in Tech.
11/13/2026
Full time
This job is with Colt Technology Services, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Colt provides network, voice and data centre services to thousands of businesses around the world, allowing them to focus on delivering their business goals instead of the underlying infrastructure. Summary Job title : Senior AI Engineer Reports to : VP of AI Technology and Architecture Job location : Must have ability to be onsite in Boulder, CO office for 2-3 days a week About Colt and the AI Practice Colt Technology Services is a global digital infrastructure company, operating one of the world's largest fiber networks across Europe and Asia. We are building a Boulder-based AI team as the engineering center of our AI Practice. The team is responsible for how AI is adopted, governed, and scaled across Colt. The AI Practice operates across several parallel workstreams, including use case delivery, AI WAN, and private AI. The Boulder team is where we build, test, and validate before we scale. Why we need this role This is a build role. You will take AI use cases from a business problem to something running in production and being used every day: retrieval and search over Colt's own data, agents that carry out multi-step work, and AI built into the systems Colt's teams already rely on. We are looking for a strong software engineer first. If you have spent eight to ten years building and running production systems and even if you have not yet shipped an LLM-based product, we want to hear from. The platform, the tooling, and the model access are already in place, and a staff-level AI engineer on the team will pair with you directly on the AI side of the work. The AI-specific skills you can bring to the table is a plus but is also learnable. The engineering experience and judgement that comes from having owned real systems in production is not, and that is the part we are hiring for. What we do expect is that you have already got hands on with AI, whether at work or as a side project for yourself. You will be working directly with the Colt teams taking requirements from them. The team is small by design, the problems are real, and what you build in your first year sets the pattern for how Colt builds AI. What you will do Build AI Use Cases Design and build AI applications end to end: data access, retrieval, model calls, orchestration, and the interfaces people use Work with large language models through APIs and self-hosted inference, covering prompting, tool use, retrieval, and multi-step agent workflows Build evaluation harnesses that show whether a use case is good enough to ship, and keep owning them after it ships Integrate AI into Colt's existing systems and data, within the constraints of a live enterprise environment Work Directly With the Business Work with the Colt teams, who will be your customers, and who will use what you build, across network operations, service delivery, finance, and others Turn a loosely described business problem into a scoped, buildable design Show working software early and often, and change direction when the first answer turns out to be wrong Be straight with stakeholders about what AI is not the right tool for Take It to Production and Keep It There Move your own work from prototype to production-grade: tested, instrumented, documented, and supportable Monitor accuracy, latency, and cost in production, and act when they drift Work with platform engineers on deployment, and hand over cleanly to production operations Contribute reusable patterns, components, and internal libraries so the next use case is faster than the last What we're looking for Engineering Experience: 8-10+ years building production software. You have owned systems end to end: designed them, shipped them, operated them, and been on the hook when they broke. Languages: Strong in Python, or strong in another language such as Java, Go, C#, or TypeScript and ready to work primarily in Python. Production Systems: APIs and service integration, working with real data at scale, testing, CI/CD, and debugging things that are already live in front of users. Cloud: Comfortable in any major cloud. We build primarily on Google Cloud; equivalent AWS or Azure experience is ok to start. Working Style: Comfortable with ambiguity and with direct contact with non-technical stakeholders. You ask what the problem is before deciding what to build. Hands-On with AI: You have already built something with it under your own steam. A side project, a prototype at work, an internal tool, a serious evaluation you ran, or agentic coding tools you use daily and have opinions about. It does not need to have shipped, been finished, or worked. We want to hear what you tried, what broke, and what you concluded. Helpful, Not Required: Any of this at enterprise scale: production RAG over messy real-world data, agent frameworks, evaluation tooling, Vertex AI, Kubernetes, Terraform. Useful if you have it, and teachable if you do not. HOW YOU WILL RAMP You pair with a staff-level AI engineer from your first week, on a live use case rather than a training exercise The AI platform is already running: model gateway, evaluation tooling, deployment pipelines, and sandbox, development, and production environments We expect you to put something small into real use inside your first 90 days, and to lead a use case end to end within six months WHEN WE TALK Come ready to walk us through something you have built with AI, however small or unfinished. We would rather see a rough prototype you can explain in depth than a polished project you cannot. Expect us to ask where it fell short, what you would do differently, and how you decided whether it was any good. How you evaluated it matters more to us than what you shipped. If you have not used AI tools in your own engineering work, this will be a difficult conversation. That is the one gap we are not set up to close for you. What we offer you: Looking to make a mark? At Colt, you'll make a difference. Because around here, we empower people. We don't tell you what to do. Instead, we employ people we trust, who come together across the globe to create intelligent solutions. Our global teams are full of ambitious, driven people, all working together towards one shared purpose: to put the power of the digital universe in the hands of our customers wherever, whenever and however they want. We give our people the opportunity to inspire and lead teams, and work on projects that connect people, cities, businesses, and ideas. We want you to help us change the world, for the better. Diversity and inclusion Inclusion and valuing diversity of thought and experience are at the heart of our culture here at Colt. From day one, you'll be encouraged to be yourself because we believe that's what helps our people to thrive. We welcome people with diverse backgrounds and experiences, regardless of their gender identity or expression, sexual orientation, race, religion, disability, neurodiversity, age, marital status, pregnancy status, or place of birth. Most recently we have: Signed the UN Women Empowerment Principles which guide our Gender Action Plan Trained 60 (and growing) Colties to be Mental Health First Aiders Please speak with a member of our recruitment team if you require adjustments to our recruitment process to support you. For more information about our Inclusion and Diversity agenda, visit our DEI pages . Benefits Our benefits support you through all parts of life, for both physical and mental health. Flexible working hours and the option to work from home. Extensive induction program with experienced mentors and buddies. Opportunities for further development and educational opportunities. Global Family Leave Policy. Employee Assistance Program. Internal inclusion & diversity employee networks. A global network When you join Colt you become part of our global network. We are proud of our colleagues and the stories and experience they bring - take a look at 'Our People' site including our Empowered Women in Tech.
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (LLM Gateway, FM Hosting) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
AI Engineer 4 (LLM Gateway, FM Hosting) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (Vision model (VLM) customization experience) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
AI Engineer 4 (Vision model (VLM) customization experience) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Sr. Staff AI Engineer (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Safety and Multimodal) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: Y ou love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are experienced in AI red teaming and in deploying safety guardrails for multimodal systems, including VLMs, MLLMs, and MM-RAG architectures You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in AI Safety and LLM safety alignment Experience with Safety and vulnerability assessment of Multi-modal application using image/video plus text modality Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
11/13/2026
Full time
AI Engineer 4 (AI Safety and Multimodal) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: Y ou love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are experienced in AI red teaming and in deploying safety guardrails for multimodal systems, including VLMs, MLLMs, and MM-RAG architectures You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in AI Safety and LLM safety alignment Experience with Safety and vulnerability assessment of Multi-modal application using image/video plus text modality Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
AI Engineer 4 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 3+ years of experience with Kubernetes Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
AI Engineer 4 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) 3+ years of experience with Kubernetes Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Foundations: World Model, RL, Causal Inference, Sequential Data) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
11/13/2026
Full time
AI Engineer 4 (AI Foundations: World Model, RL, Causal Inference, Sequential Data) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Sr. Staff AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
AI Engineer 4 (Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Foundations: World Model, RL, Causal Inference, Sequential Data) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
11/13/2026
Full time
AI Engineer 4 (AI Foundations: World Model, RL, Causal Inference, Sequential Data) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
