37 jobs found

Job Description Job Description Description: About Us: eSimplicity is a modern digital services company that partners with government agencies to improve the lives and protect the well-being of all Americans, from veterans and service members to children, families, and seniors. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that equip federal agencies with solutions to courageously transform today for a better tomorrow. Responsibilities: The Agentic AI & MCP Specialist will architect, develop, and operationalize next-generation agentic systems powered by advanced LLMs and Model Context Protocol (MCP) frameworks. This role focuses on building intelligent, multi-step, tool-using agents that can autonomously reason, plan, and execute complex workflows across a cloud-based analytics ecosystem. The specialist will design and implement agent orchestration frameworks, integrate model-driven decision logic, and build robust, production-grade agent capabilities that safely leverage emerging AI techniques. This position requires a deeply skilled software developer who combines strong engineering fundamentals with hands-on experience creating agentic systems, working with MCP-based integrations, designing LLM-driven tools, and building secure, scalable AI applications. The role provides technical leadership, explores cutting-edge agentic patterns, drives proof-of-concept innovation, and partners with engineering and product teams to translate experimental architectures into real-world impact. Requirements: Required Qualifications: All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation. Bachelor's Degree and 10+ years of software engineering experience Experience designing, developing, and supporting production applications, platforms, or services. Experience developing agentic AI solutions, including planning, tool utilization, workflow orchestration, multi-step reasoning, or autonomous task execution. Experience designing and implementing Model Context Protocol (MCP) integrations, tool interfaces, or model-driven service architectures. Ability to analyze business, customer, or mission requirements and develop scalable AI-driven solutions that align with technical and operational objectives. Experience with large language model (LLM) development practices, including fine-tuning, retrieval-augmented generation (RAG), prompt engineering, and agent interaction patterns. Proficiency in Python and experience working with APIs, microservices, distributed computing environments, and cloud-native architectures. Experience deploying and integrating AI agents or LLM-enabled applications within cloud environments such as Azure, AWS, or Google Cloud Platform (GCP). Knowledge of MLOps and LLMOps practices, including model versioning, automated testing, deployment automation, monitoring, performance evaluation, and governance. Ability to contribute to solution design discussions, provide technical guidance to team members, and communicate AI-related concepts to technical and non-technical audiences. Experience using version control systems and CI/CD practices, including source code management, automated testing, deployment pipelines, and release management for production environments. Desired Qualifications: Experience building multi-agent systems, agent swarms, or coordinated reasoning frameworks. Familiarity with advanced tool-calling strategies, including dynamic tool selection, function-call planning, or graph-structured task planners. Experience with structured LLM evaluation methods, agent benchmarking, or test harnesses for autonomous systems. Knowledge of performance optimization techniques for LLMs and agents, including caching, model distillation, model routing, or accelerated inference. Background integrating agentic components with large-scale data or analytics platforms (e.g., Databricks, Snowflake, Spark). Hands-on experience developing innovative POCs or experimental agentic architectures in fast-paced R&D environments. Familiarity with emerging agentic frameworks such as Strands Agents, LangGraph, CrewAI, etc. Exposure to safety-oriented design patterns for autonomous systems, including guardrails, validation layers, or constrained-action frameworks. Experience designing and building secure, compliance-aware systems that handle sensitive data in accordance with HIPAA and federal security standards, including implementation of encryption, access controls, auditability, and governance for protected health information (PHI) within AI/LLM workflows. Working Environment : eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by manager. Occasional travel for training and project meetings. It is estimated to be less than 5% per year. Benefits: eSimplicity offers a comprehensive benefits package, including medical, dental, and vision coverage, 401(k) retirement benefits, paid time off, paid holidays, life and disability insurance, and additional wellness and employee support programs. Eligibility may vary based on employment status and applicable plan terms. Reasonable Accommodation: eSimplicity is committed to providing reasonable accommodations to qualified individuals with disabilities during the application and hiring process. Applicants who need assistance or an accommodation should contact Human Resources. Equal Employment Opportunity: eSimplicity is an Equal Opportunity Employer, including disability and protected veteran status. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran status, disability, or any othe

Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.

Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in San Francisco, Bay Area. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.

Job Description Job Description Why Charlie Health? Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported. Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection-between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home. As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you. About the Role Core Platform is a platform team. Our customers are Charlie Health's other engineering teams, and our job is to make them faster, safer, and more consistent. We don't ship product features. We build the patterns, services, and guardrails that other engineering teams depend on. As the Principal Platform Engineer on Core Platform, you will be the technical lead for the team building the platform underneath everything Charlie Health ships next: a federated GraphQL front door that fronts every client surface, the event substrate that carries every signal, the identity layer that authenticates every human and every AI agent, and the real-time world model state layer that gives our services and agents a live picture of care. You will be foundational in a replatforming effort, and the primitives you design become the platform's paved roads. This is a technical leadership role without direct reports. You own the team's technical direction, roadmap, and delivery. You will set direction for a team of Staff and Senior Platform Engineers, make the hardest design calls of the replatforming, and stay hands-on in the work. We build with AI as the default. Specs are the primary artifact, agents draft most of the implementation, and the quality gates this team owns are what make that safe in a HIPAA-regulated clinical business. Responsibilities Own the team's roadmap and intake. Balance incoming platform requests and near-term developer pain against long-term architectural investment, with support from the Director of Platform Engineering and the CTO Set the technical direction for the Core Platform team and break the north star architecture into projects the team ships quarter by quarter Run the team's delivery: planning, refinement, and the sprint cadence, with epics scoped to clear milestones and target dates Architect the federated GraphQL supergraph and govern its schema, including subgraph onboarding standards, contract enforcement, and caching and persisted query posture Build authentication and authorization for the platform, including agent identity: scoped, short-lived, audited credentials for non-human principals Design, build, and operate the centralized event substrate, including schema governance, dead-letter conventions, and the producer and consumer patterns that make async the default integration path between services Guide the technical execution of our strangler-fig migration through to cutover, working with product squads as they move onto the new platform Deliver the real-time world model state layer: the stream processing that turns events into state, and the live, low-latency state graph that services and agents query Facilitate the Architecture Advice Guild rituals and provide technical direction on architecture decision records for cross-team decisions and standards Raise the bar for spec writing and agent orchestration on the team, and review specs and agent output with the same rigor you would apply to a senior engineer's work Keep the platform services the team operates reliable: SLOs, monitor-gated deploys, incident leadership, and a seat in the on-call rotation Drive the technical evaluation for procurement and renewals of our critical platform vendors: evaluations, proofs of concept, usage and cost data, and build versus buy recommendations, partnering with the Director who owns the commercial side Mentor Staff and Senior engineers toward larger scope Requirements 10+ years of software engineering experience, including ownership of platform or distributed systems architecture at company scale. You have designed, operated, and evolved systems that other teams build on Hands-on experience with GraphQL federation at scale and with event streaming systems such as Kafka, covering design, schema governance, and production operation rather than just consumption Experience with skills, MCPs, harnesses, agentic tooling ecosystems, or agent orchestration for software development A track record of technical leadership without people authority. You have aligned multiple teams behind architectural outcomes and developed senior engineers Experience owning a team roadmap: intake, prioritization, and delivery planning alongside the architecture work You build with AI agents as part of your daily work. You write specs agents can implement, run agents for real delivery, and know where agent output needs human judgment Proficiency in the stack we run: TypeScript and/or Python services, Postgres, and AWS managed primitives Comfort operating production critical-path systems, including on-call, in a regulated environment Clear, direct communication with engineers, leadership, clinicians, and compliance This role requires 4 days per week in our NYC office. Nice to Haves Real-time stream processing (Flink, Spark, KsqlDB, or similar) and graph databases (Memgraph, Neo4j, Amazon Neptune, Dgraph, or similar) Healthcare data standards (FHIR, HL7v2) and engineering in a HIPAA-regulated environment Time as a people manager for senior or staff level engineers A strangler-fig migration or large platform cutover you have led Prior work on a platform engineering team Fluency with domain-driven design or event storming Benefits Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here. The total target base compensation for this role will be between $225,000 and $325,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. Our Values Connection: Care deeply & inspire hope. Congruence: Stay curious & heed the evidence. Commitment: Act with urgency & don't give up. Please do not call our public clinical admissions line in regard to this or any other job posting. Please be cautious of potential recruitment fraud. If you are interested in exploring opportunities at Charlie Health, please go directly to our Careers Page: -openings. Charlie Health will never ask you to pay a fee or download software as part of the interview process with our company. In addition, Charlie Health will not ask for your personal banking information until you have signed an offer of employment and completed onboarding paperwork that is provided by our People Operations team. All communications with Charlie Health Talent and People Operations professionals will only be sent email addresses. Legitimate emails will never originate from or other commercial email services. Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals. At Charlie Health, we value being an Equal Opportunity Employer. We strive to cultivate an environment where individuals can be their authentic selves. Being an Equal Opportunity Employer means every member of our team feels as though they are supported and belong. We value diverse perspectives to help us provide essential mental health and substance use disorder treatments to all young people. Charlie Health applicants are assessed solely on their qualifications for the role, without regard to disability or need for accommodation. By clicking "Submit application" below, you agree to Charlie Health's Privacy Policy and Terms of Service. By submitting your application, you agree to receive SMS messages from Charlie Health regarding your application. Message and data rates may apply. Message frequency varies. You can reply STOP to opt out at any time. For help, reply HELP.

Job Description Job Description Why Charlie Health? Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they're met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported. Charlie Health exists to change that. Our mission is to connect the world to life-saving behavioral health treatment. We deliver personalized, virtual care rooted in connection-between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we're expanding access to meaningful care and driving better outcomes from the comfort of home. As a rapidly growing organization, we're reaching more communities every day and building a team that's redefining what behavioral health treatment can look like. If you're ready to use your skills to drive lasting change and help more people access the care they deserve, we'd love to meet you. About the Role Core Platform is a platform team. Our customers are Charlie Health's other engineering teams, and our job is to make them faster, safer, and more consistent. We don't ship product features. We build the patterns, services, and guardrails that other engineering teams depend on. As the Principal Platform Engineer on Core Platform, you will be the technical lead for the team building the platform underneath everything Charlie Health ships next: a federated GraphQL front door that fronts every client surface, the event substrate that carries every signal, the identity layer that authenticates every human and every AI agent, and the real-time world model state layer that gives our services and agents a live picture of care. You will be foundational in a replatforming effort, and the primitives you design become the platform's paved roads. This is a technical leadership role without direct reports. You own the team's technical direction, roadmap, and delivery. You will set direction for a team of Staff and Senior Platform Engineers, make the hardest design calls of the replatforming, and stay hands-on in the work. We build with AI as the default. Specs are the primary artifact, agents draft most of the implementation, and the quality gates this team owns are what make that safe in a HIPAA-regulated clinical business. Responsibilities Own the team's roadmap and intake. Balance incoming platform requests and near-term developer pain against long-term architectural investment, with support from the Director of Platform Engineering and the CTO Set the technical direction for the Core Platform team and break the north star architecture into projects the team ships quarter by quarter Run the team's delivery: planning, refinement, and the sprint cadence, with epics scoped to clear milestones and target dates Architect the federated GraphQL supergraph and govern its schema, including subgraph onboarding standards, contract enforcement, and caching and persisted query posture Build authentication and authorization for the platform, including agent identity: scoped, short-lived, audited credentials for non-human principals Design, build, and operate the centralized event substrate, including schema governance, dead-letter conventions, and the producer and consumer patterns that make async the default integration path between services Guide the technical execution of our strangler-fig migration through to cutover, working with product squads as they move onto the new platform Deliver the real-time world model state layer: the stream processing that turns events into state, and the live, low-latency state graph that services and agents query Facilitate the Architecture Advice Guild rituals and provide technical direction on architecture decision records for cross-team decisions and standards Raise the bar for spec writing and agent orchestration on the team, and review specs and agent output with the same rigor you would apply to a senior engineer's work Keep the platform services the team operates reliable: SLOs, monitor-gated deploys, incident leadership, and a seat in the on-call rotation Drive the technical evaluation for procurement and renewals of our critical platform vendors: evaluations, proofs of concept, usage and cost data, and build versus buy recommendations, partnering with the Director who owns the commercial side Mentor Staff and Senior engineers toward larger scope Requirements 10+ years of software engineering experience, including ownership of platform or distributed systems architecture at company scale. You have designed, operated, and evolved systems that other teams build on Hands-on experience with GraphQL federation at scale and with event streaming systems such as Kafka, covering design, schema governance, and production operation rather than just consumption Experience with skills, MCPs, harnesses, agentic tooling ecosystems, or agent orchestration for software development A track record of technical leadership without people authority. You have aligned multiple teams behind architectural outcomes and developed senior engineers Experience owning a team roadmap: intake, prioritization, and delivery planning alongside the architecture work You build with AI agents as part of your daily work. You write specs agents can implement, run agents for real delivery, and know where agent output needs human judgment Proficiency in the stack we run: TypeScript and/or Python services, Postgres, and AWS managed primitives Comfort operating production critical-path systems, including on-call, in a regulated environment Clear, direct communication with engineers, leadership, clinicians, and compliance This role requires 4 days per week in our NYC office. Nice to Haves Real-time stream processing (Flink, Spark, KsqlDB, or similar) and graph databases (Memgraph, Neo4j, Amazon Neptune, Dgraph, or similar) Healthcare data standards (FHIR, HL7v2) and engineering in a HIPAA-regulated environment Time as a people manager for senior or staff level engineers A strangler-fig migration or large platform cutover you have led Prior work on a platform engineering team Fluency with domain-driven design or event storming Benefits Charlie Health is pleased to offer comprehensive benefits to all full-time, exempt employees. Read more about our benefits here. The total target base compensation for this role will be between $225,000 and $325,000 per year at the commencement of employment. Please note, pay will be determined on an individualized basis and will be impacted by location, experience, expertise, internal pay equity, and other relevant business considerations. Further, cash compensation is only part of the total compensation package, which, depending on the position, may include stock options and other Charlie Health-sponsored benefits. Our Values Connection: Care deeply & inspire hope. Congruence: Stay curious & heed the evidence. Commitment: Act with urgency & don't give up. Please do not call our public clinical admissions line in regard to this or any other job posting. Please be cautious of potential recruitment fraud. If you are interested in exploring opportunities at Charlie Health, please go directly to our Careers Page: -openings. Charlie Health will never ask you to pay a fee or download software as part of the interview process with our company. In addition, Charlie Health will not ask for your personal banking information until you have signed an offer of employment and completed onboarding paperwork that is provided by our People Operations team. All communications with Charlie Health Talent and People Operations professionals will only be sent email addresses. Legitimate emails will never originate from or other commercial email services. Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals. At Charlie Health, we value being an Equal Opportunity Employer. We strive to cultivate an environment where individuals can be their authentic selves. Being an Equal Opportunity Employer means every member of our team feels as though they are supported and belong. We value diverse perspectives to help us provide essential mental health and substance use disorder treatments to all young people. Charlie Health applicants are assessed solely on their qualifications for the role, without regard to disability or need for accommodation. By clicking "Submit application" below, you agree to Charlie Health's Privacy Policy and Terms of Service. By submitting your application, you agree to receive SMS messages from Charlie Health regarding your application. Message and data rates may apply. Message frequency varies. You can reply STOP to opt out at any time. For help, reply HELP.

Job Description Job Description Staff / Principal Platform Engineer Location: New York City Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization's most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate's AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We're looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate's AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You'll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you'll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate's AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must. Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management. Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust. Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality. Integrations: third-party connectors, APIs and platform integrations. Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management. Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly. Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship. Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate's strategic vision. Required Qualifications Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact. DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS). Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice. Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale. Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems. Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on. Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring. Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions - TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling - and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation Staff: 185k-225k base Principal: 215k-270k base We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate's policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company's EEO Coordinator.

AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 5 (AI Foundations) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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. McLean, VA: $229,900 - $262,400 for AI Engineer 5 Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 5 (GenAI Platform Services, Agentic Platform) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 5 (Gen AI Platform Services - Agentic AI) Overview: 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 (SDK's: Gen AI Evaluation and MCP) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 (GenAI Platform Services, Agentic Platform) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 5 (AI Foundations, LLM Core and 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 5 (SDK's: Gen AI Evaluation and MCP) 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 . click apply for full job details

AI Engineer 5 (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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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 5 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. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity 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 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 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 7 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 complex AI systems 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 Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression 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: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 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