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applied ai engineer agentic workflows
Forward Deployed AI Engineer (In Training)
Turing New York, New York
Job Description Job Description About Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at . Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you'll define the frontier by building beyond it. You'll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world's leading enterprises. As a Forward-Deployed AI Engineer (In Training), you'll own outcomes end to end-from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You'll build generative AI solutions in the real world that drive measurable business impact and return on investment within large institutions. Your first placement will be in Turing Akademia , where you'll build the applied AI, production engineering, and client-delivery skills required for the role. Candidates who successfully complete this placement will be immediately placed on live Turing Enterprise AI client projects as full-time Forward-Deployed AI Engineers with Turing. Turing Akademia is an eight-week intensive development experience for high-performing software engineers and full-stack developers who are close to being ready for forward-deployed work. Through hands-on technical training, production-oriented projects, and direct feedback, you'll strengthen the skills required to build reliable AI systems and deliver solutions in complex client environments. Enterprise AI is intense, intellectually challenging work. It won't be for everyone, but it may be exactly the challenge you're looking for. As a Forward-Deployed Engineer, You WillFind the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, and use curiosity and business acumen to understand their workflows and jointly define the business outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems-from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Complete your first placement in Turing Akademia, building and demonstrating these capabilities through intensive, hands-on work. Own the Outcome You won't simply be given a list of responsibilities-you'll have the authority to own the outcome for your client and make a real-world impact through your work. Present your work to stakeholders, manage expectations, explain technical decisions, and respond constructively to pushback. Lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. Your first placement in Turing Akademia will be demanding, fast-paced, and feedback-heavy, preparing you for clients with uncompromising expectations for quality. Client-first and in-person: Our work is client-first, which means in-office collaboration may be required either at the client site or at our planned Manhattan office near Madison Square Park. Depending on your assignment and client needs, you should expect to work in person three to five days per week and be based in the New York City area or within a reasonable commuting distance. You'll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you'll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Strong production engineering experience: Typically 5+ years as a software engineer or full-stack developer building production or near-production systems. Strong technical foundation: Experience with programming, APIs, databases, backend systems, cloud infrastructure, and software development practices. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Ownership and learning agility: A history of taking initiative, solving unstructured problems, responding well to feedback, and learning new technologies quickly. Prior experience with AI, LLMs, RAG, or agentic systems is helpful but not required. Your first placement in Turing Akademia is designed to build those skills. Role: Forward-Deployed AI Engineer - In Training Location: New York City Experience Level: 5+ years as a full-stack developer Compensation: $170,000-$210,000 base salary + equity Work Model: In-office, typically three to five days per week, depending on client requirements Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.
10/25/2026
Full time
Job Description Job Description About Turing Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at . Why Join Enterprise AI? Enterprise AI is a distinct business unit within Turing, operating with the speed, focus, and ownership of a rapidly scaling startup. When it comes to applied AI in the workplace, you'll define the frontier by building beyond it. You'll join the initial team of Forward-Deployed Engineers, shaping how we work while solving enterprise-grade problems for the world's leading enterprises. As a Forward-Deployed AI Engineer (In Training), you'll own outcomes end to end-from identifying high-value customer problems and shaping architecture to building production systems and working directly with senior client leaders. You'll build generative AI solutions in the real world that drive measurable business impact and return on investment within large institutions. Your first placement will be in Turing Akademia , where you'll build the applied AI, production engineering, and client-delivery skills required for the role. Candidates who successfully complete this placement will be immediately placed on live Turing Enterprise AI client projects as full-time Forward-Deployed AI Engineers with Turing. Turing Akademia is an eight-week intensive development experience for high-performing software engineers and full-stack developers who are close to being ready for forward-deployed work. Through hands-on technical training, production-oriented projects, and direct feedback, you'll strengthen the skills required to build reliable AI systems and deliver solutions in complex client environments. Enterprise AI is intense, intellectually challenging work. It won't be for everyone, but it may be exactly the challenge you're looking for. As a Forward-Deployed Engineer, You WillFind the Problem Worth Solving Work directly with customers to navigate ambiguity, uncover high-value opportunities, and use curiosity and business acumen to understand their workflows and jointly define the business outcomes an AI solution should drive. Build Beyond the Frontier Architect and build production AI systems-from multi-agent workflows, orchestration, tool use, context engineering, memory and state, and retrieval-augmented generation (RAG) to the APIs, data pipelines, integrations, and distributed systems that make them reliable at scale. Complete your first placement in Turing Akademia, building and demonstrating these capabilities through intensive, hands-on work. Own the Outcome You won't simply be given a list of responsibilities-you'll have the authority to own the outcome for your client and make a real-world impact through your work. Present your work to stakeholders, manage expectations, explain technical decisions, and respond constructively to pushback. Lead solutions from discovery through deployment and measurable impact while staying hands-on and owning evaluation, observability, security, reliability, latency, scalability, and cost. The Anti-Sell High ownership and intensity: This role requires exceptional ownership and accountability. Your first placement in Turing Akademia will be demanding, fast-paced, and feedback-heavy, preparing you for clients with uncompromising expectations for quality. Client-first and in-person: Our work is client-first, which means in-office collaboration may be required either at the client site or at our planned Manhattan office near Madison Square Park. Depending on your assignment and client needs, you should expect to work in person three to five days per week and be based in the New York City area or within a reasonable commuting distance. You'll help write the playbook: Enterprise AI operates like a startup. You may not always have an established process or playbook because you'll be expected to apply your expertise, judgment, and technical depth to create one. Our Forward-Deployed Engineers Typically Have Strong production engineering experience: Typically 5+ years as a software engineer or full-stack developer building production or near-production systems. Strong technical foundation: Experience with programming, APIs, databases, backend systems, cloud infrastructure, and software development practices. Client-ready communication: The ability to explain technical concepts clearly, navigate ambiguity, work with stakeholders, and remain calm under pressure. Ownership and learning agility: A history of taking initiative, solving unstructured problems, responding well to feedback, and learning new technologies quickly. Prior experience with AI, LLMs, RAG, or agentic systems is helpful but not required. Your first placement in Turing Akademia is designed to build those skills. Role: Forward-Deployed AI Engineer - In Training Location: New York City Experience Level: 5+ years as a full-stack developer Compensation: $170,000-$210,000 base salary + equity Work Model: In-office, typically three to five days per week, depending on client requirements Values We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity. Advantages of joining Turing Work at the frontier of AI , helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. Bring frontier AI innovation to the enterprise , applying lessons learned from leading AI labs to solve real-world business challenges. Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. Move at the pace of AI innovation , with the speed, ownership, and impact of a startup. Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. For applicants from the European Union, please review Turing's GDPR notice here.
Applied AI Lead Developer
Family Dollar Chesapeake, Virginia
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar
10/25/2026
Full time
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar
Founding Applied AI Engineer- Proactive AI Agents
Morgan Pinnacle Group San Francisco, California
Job Description Job Description Founding Applied AI Engineer - Proactive AI Agents Location: San Francisco, CA Work Arrangement: Onsite, 5 days/week Employment Type: Full-time Base Salary: 300K-500K Equity: Substantial founding-level equity Visa: Open to visa transfers and new sponsorship Relocation: Relocation support available About the Opportunity An early-stage, research-first AI company is building the next generation of personal, proactive AI agents. Rather than creating another chatbot or copilot that waits for instructions, the team is developing agents that learn how people work, understand intent, anticipate needs, and autonomously pursue objectives on their behalf. The product observes the context naturally created during work-including screen activity, conversations, and actions across tools-to understand what users are trying to accomplish and how they make decisions. It uses those signals to automate repetitive workflows and proactively identify opportunities to advance users' goals. This is a ground-floor opportunity to join a three-person founding team and help shape the product, technical architecture, and engineering culture from the beginning. The Role We're looking for a Founding Applied AI Engineer who has already built and shipped AI-powered products hands-on. You'll own 01 product areas end-to-end, working across user-facing products, agent workflows, model orchestration, and infrastructure. This is a high-agency environment. You'll be expected to make important technical and product decisions independently, move quickly, work closely with users, and take responsibility for outcomes rather than simply implementing predefined specifications. What You'll Do Own and ship zero-to-one AI product areas end-to-end Build and iterate on agent harnesses and agentic systems that observe user behavior, learn intent, and automate workflows Work across user-facing interfaces, agent workflows, models, orchestration, and infrastructure Make independent technical and product decisions around system design, reliability, and shipping speed Work directly with users and enterprise customers to understand workflows Rapidly prototype and iterate on solutions Help shape product vision, technical architecture, and company culture What We're Looking For Core requirements Experience at an AI lab, applied AI startup, or infrastructure company Hands-on experience owning and shipping a 01 ML/AI model-based product or agentic system to production Hands-on experience building agentic systems, agent harnesses, or model-based AI/ML products Deep professional expertise with Python Ability to operate across product, engineering, models, and infrastructure Ability to contribute to product vision, ideation, and feature definition Ability to work onsite in San Francisco 5 days per week The target profile has 2-6 years of experience as an Applied AI Engineer . Strong Additional Signals Early-stage startup engineering experience Founder experience Early-hire experience at a high-growth AI startup Major end-to-end product ownership Strong academic background from a top-tier global institution Tech Stack Python, LLMs, agent frameworks, model orchestration, production ML systems. Working Environment This is a small, high-intensity founding environment built around extreme ownership, speed, high agency, and close collaboration. Engineers operate across research and product development rather than staying inside narrowly defined functions. Team members are expected to make strong technical and product decisions independently and help define what gets built. The team works together five days per week in San Francisco . Compensation & Equity 300K- 500K base salary + substantial founding-level equity. Compensation is benchmarked to candidate market value rather than years of experience alone. Visa & Relocation The company is open to: Visa transfers, including OPT and H-1B transfers New sponsorship, including H-1B and TN Relocation for candidates outside San Francisco Client Interview Process (after candidates are submitted to the client) Stage 1 - CEO Intro Call 30 minutes Virtual Conversation covering your background, motivation, mission alignment, interest in the company's vision, and what you're looking for. Stage 2 - Technical Interview 45-60 minutes Virtual Depending on your background, this may include system design, a deep dive into a feature or system you've owned, or a broader technical conversation. The team will evaluate hands-on technical depth, engineering judgment, and understanding of AI/agent systems. Stage 3 - Onsite Final 3-4 hours San Francisco A half-day onsite including conversations with the team, a work trial or collaborative exercise, and an opportunity to experience the working environment.
10/24/2026
Full time
Job Description Job Description Founding Applied AI Engineer - Proactive AI Agents Location: San Francisco, CA Work Arrangement: Onsite, 5 days/week Employment Type: Full-time Base Salary: 300K-500K Equity: Substantial founding-level equity Visa: Open to visa transfers and new sponsorship Relocation: Relocation support available About the Opportunity An early-stage, research-first AI company is building the next generation of personal, proactive AI agents. Rather than creating another chatbot or copilot that waits for instructions, the team is developing agents that learn how people work, understand intent, anticipate needs, and autonomously pursue objectives on their behalf. The product observes the context naturally created during work-including screen activity, conversations, and actions across tools-to understand what users are trying to accomplish and how they make decisions. It uses those signals to automate repetitive workflows and proactively identify opportunities to advance users' goals. This is a ground-floor opportunity to join a three-person founding team and help shape the product, technical architecture, and engineering culture from the beginning. The Role We're looking for a Founding Applied AI Engineer who has already built and shipped AI-powered products hands-on. You'll own 01 product areas end-to-end, working across user-facing products, agent workflows, model orchestration, and infrastructure. This is a high-agency environment. You'll be expected to make important technical and product decisions independently, move quickly, work closely with users, and take responsibility for outcomes rather than simply implementing predefined specifications. What You'll Do Own and ship zero-to-one AI product areas end-to-end Build and iterate on agent harnesses and agentic systems that observe user behavior, learn intent, and automate workflows Work across user-facing interfaces, agent workflows, models, orchestration, and infrastructure Make independent technical and product decisions around system design, reliability, and shipping speed Work directly with users and enterprise customers to understand workflows Rapidly prototype and iterate on solutions Help shape product vision, technical architecture, and company culture What We're Looking For Core requirements Experience at an AI lab, applied AI startup, or infrastructure company Hands-on experience owning and shipping a 01 ML/AI model-based product or agentic system to production Hands-on experience building agentic systems, agent harnesses, or model-based AI/ML products Deep professional expertise with Python Ability to operate across product, engineering, models, and infrastructure Ability to contribute to product vision, ideation, and feature definition Ability to work onsite in San Francisco 5 days per week The target profile has 2-6 years of experience as an Applied AI Engineer . Strong Additional Signals Early-stage startup engineering experience Founder experience Early-hire experience at a high-growth AI startup Major end-to-end product ownership Strong academic background from a top-tier global institution Tech Stack Python, LLMs, agent frameworks, model orchestration, production ML systems. Working Environment This is a small, high-intensity founding environment built around extreme ownership, speed, high agency, and close collaboration. Engineers operate across research and product development rather than staying inside narrowly defined functions. Team members are expected to make strong technical and product decisions independently and help define what gets built. The team works together five days per week in San Francisco . Compensation & Equity 300K- 500K base salary + substantial founding-level equity. Compensation is benchmarked to candidate market value rather than years of experience alone. Visa & Relocation The company is open to: Visa transfers, including OPT and H-1B transfers New sponsorship, including H-1B and TN Relocation for candidates outside San Francisco Client Interview Process (after candidates are submitted to the client) Stage 1 - CEO Intro Call 30 minutes Virtual Conversation covering your background, motivation, mission alignment, interest in the company's vision, and what you're looking for. Stage 2 - Technical Interview 45-60 minutes Virtual Depending on your background, this may include system design, a deep dive into a feature or system you've owned, or a broader technical conversation. The team will evaluate hands-on technical depth, engineering judgment, and understanding of AI/agent systems. Stage 3 - Onsite Final 3-4 hours San Francisco A half-day onsite including conversations with the team, a work trial or collaborative exercise, and an opportunity to experience the working environment.
Novartis
Associate Director, Semantic & Knowledge Engineering (2 Openings)
Novartis East Hanover, New Jersey
This job is with Novartis, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Summary Reporting to the Executive Director, Semantic and Knowledge Engineering, the Associate Director, Semantic and Knowledge Engineering designs, builds, and governs enterprise semantic models, ontologies, taxonomies, business vocabularies, knowledge graphs, metadata services, and semantic APIs. The role enables AI, analytics, enterprise search, interoperability, retrieval-augmented generation (RAG), agentic AI, contextual search, and reasoning engines by embedding reusable semantic capabilities into products and workflows across Strategy, Platforms & Transformation. The ideal location for this role is East Hanover but remote work may be possible (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. If associate is remote, all home office expenses and any travel/lodging to specific East Hanover for periodic live meetings will be at the employee's expense. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 10% travel. There are 2 positions available. About the Role Key Responsibilities : Enterprise semantic modeling and knowledge engineering • Design, develop, and maintain enterprise ontologies, taxonomies, business vocabularies, and semantic models that establish consistent meaning across products, data, and AI capabilities. • Build and enhance knowledge graphs, metadata services, and semantic APIs that support AI, analytics, enterprise applications, and commercial decision enablement. Semantic capabilities for AI and product workflows • Collaborate with Product, Applied AI, Analytics Engineering, and Platform Engineering teams to embed semantic capabilities into products, workflows, platforms, and reusable solution patterns. • Support semantic foundations for RAG, agentic AI, contextual search, reasoning engines, enterprise search, analytics, and interoperability initiatives. Metadata governance and knowledge lifecycle management • Implement metadata governance, semantic quality controls, stewardship practices, and lifecycle management for enterprise knowledge assets. • Promote quality, consistency, reuse, transparency, and governed evolution of semantic assets across the SPT ecosystem. Technology evaluation and architecture evolution • Evaluate emerging semantic technologies, standards, graph capabilities, and knowledge engineering approaches to inform the evolution of the enterprise knowledge architecture. • Contribute reusable engineering patterns and technical guidance that reduce duplication and improve scalability across semantic and knowledge engineering work. Technical mentorship and cross-functional collaboration • Mentor semantic and knowledge engineers while promoting reusable engineering patterns, technical excellence, disciplined documentation, and pragmatic implementation. • Communicate technical trade-offs, risks, dependencies, and recommendations clearly to product, engineering, analytics, AI, and business stakeholders. Essential Requirements: Education: Bachelor's degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, or a related discipline; advanced degree preferred. 6+ years of progressive experience in semantic technologies, knowledge engineering, metadata management, data/information architecture, data product engineering, or AI-enabling data platforms. Hands-on experience designing and maintaining ontologies, taxonomies, controlled vocabularies, business glossaries, semantic models, RDF/OWL, SKOS, SPARQL, graph databases, knowledge graphs, metadata catalogs, data lineage, and semantic APIs/services. Experience building semantic assets that enable AI grounding, RAG/GraphRAG, enterprise search, contextual search, reasoning engines, analytics consistency, interoperability, and reusable product capabilities. Working knowledge of data governance, stewardship models, provenance, quality controls, access/security controls, lifecycle management, privacy, and compliance expectations for enterprise knowledge assets. Ability to translate complex business/domain concepts into reusable semantic models and partner effectively with Product, Applied AI, Analytics Engineering, Platform Engineering, Architecture, and business domain experts. Strong engineering delivery discipline, including documentation, versioning, validation/testing of semantic assets, standards adherence, backlog execution, reusable patterns, and pragmatic implementation in agile/product teams. Strong analytical, communication, stakeholder management, and collaboration skills, with the ability to explain semantic design choices, technical trade-offs, risks, and dependencies to technical and non-technical stakeholders. Desirable Requirements: Experience applying semantic technologies in pharmaceutical, healthcare, life sciences, commercial, clinical, medical, real-world data, or another regulated data environment. Experience supporting generative AI, agentic AI, LLM-powered products, RAG/GraphRAG, vector databases, graph-enhanced retrieval, knowledge graph embeddings, enterprise search, or AI-ready semantic layers. Familiarity with FAIR data principles, master/reference data modernization, metadata platform roadmaps, ontology governance forums, stewardship operating models, and enterprise knowledge architecture practices. Experience with cloud-based data and AI ecosystems, graph/vector tooling, semantic layer technologies, API-based semantic services, and integration with enterprise search or analytics platforms. Experience mentoring junior semantic/knowledge engineers, shaping reusable engineering patterns, and contributing to technical standards or communities of practice. Advanced degree or relevant certification in Computer Science, Information Science, Data Science, Artificial Intelligence, Bioinformatics, Knowledge Engineering, Ontology Engineering, or a related discipline. Novartis Compensation Summary: The salary for this position is expected to range between $176,400 and $327,600 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together? Benefits and Rewards: Learn about all the ways we'll help you thrive personally and professionally. Read our handbook (PDF 30 MB) EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. Accessibility & Reasonable Accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to email protected or call + and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
10/24/2026
Full time
This job is with Novartis, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Summary Reporting to the Executive Director, Semantic and Knowledge Engineering, the Associate Director, Semantic and Knowledge Engineering designs, builds, and governs enterprise semantic models, ontologies, taxonomies, business vocabularies, knowledge graphs, metadata services, and semantic APIs. The role enables AI, analytics, enterprise search, interoperability, retrieval-augmented generation (RAG), agentic AI, contextual search, and reasoning engines by embedding reusable semantic capabilities into products and workflows across Strategy, Platforms & Transformation. The ideal location for this role is East Hanover but remote work may be possible (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. If associate is remote, all home office expenses and any travel/lodging to specific East Hanover for periodic live meetings will be at the employee's expense. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 10% travel. There are 2 positions available. About the Role Key Responsibilities : Enterprise semantic modeling and knowledge engineering • Design, develop, and maintain enterprise ontologies, taxonomies, business vocabularies, and semantic models that establish consistent meaning across products, data, and AI capabilities. • Build and enhance knowledge graphs, metadata services, and semantic APIs that support AI, analytics, enterprise applications, and commercial decision enablement. Semantic capabilities for AI and product workflows • Collaborate with Product, Applied AI, Analytics Engineering, and Platform Engineering teams to embed semantic capabilities into products, workflows, platforms, and reusable solution patterns. • Support semantic foundations for RAG, agentic AI, contextual search, reasoning engines, enterprise search, analytics, and interoperability initiatives. Metadata governance and knowledge lifecycle management • Implement metadata governance, semantic quality controls, stewardship practices, and lifecycle management for enterprise knowledge assets. • Promote quality, consistency, reuse, transparency, and governed evolution of semantic assets across the SPT ecosystem. Technology evaluation and architecture evolution • Evaluate emerging semantic technologies, standards, graph capabilities, and knowledge engineering approaches to inform the evolution of the enterprise knowledge architecture. • Contribute reusable engineering patterns and technical guidance that reduce duplication and improve scalability across semantic and knowledge engineering work. Technical mentorship and cross-functional collaboration • Mentor semantic and knowledge engineers while promoting reusable engineering patterns, technical excellence, disciplined documentation, and pragmatic implementation. • Communicate technical trade-offs, risks, dependencies, and recommendations clearly to product, engineering, analytics, AI, and business stakeholders. Essential Requirements: Education: Bachelor's degree in Computer Science, Information Science, Artificial Intelligence, Data Science, Bioinformatics, or a related discipline; advanced degree preferred. 6+ years of progressive experience in semantic technologies, knowledge engineering, metadata management, data/information architecture, data product engineering, or AI-enabling data platforms. Hands-on experience designing and maintaining ontologies, taxonomies, controlled vocabularies, business glossaries, semantic models, RDF/OWL, SKOS, SPARQL, graph databases, knowledge graphs, metadata catalogs, data lineage, and semantic APIs/services. Experience building semantic assets that enable AI grounding, RAG/GraphRAG, enterprise search, contextual search, reasoning engines, analytics consistency, interoperability, and reusable product capabilities. Working knowledge of data governance, stewardship models, provenance, quality controls, access/security controls, lifecycle management, privacy, and compliance expectations for enterprise knowledge assets. Ability to translate complex business/domain concepts into reusable semantic models and partner effectively with Product, Applied AI, Analytics Engineering, Platform Engineering, Architecture, and business domain experts. Strong engineering delivery discipline, including documentation, versioning, validation/testing of semantic assets, standards adherence, backlog execution, reusable patterns, and pragmatic implementation in agile/product teams. Strong analytical, communication, stakeholder management, and collaboration skills, with the ability to explain semantic design choices, technical trade-offs, risks, and dependencies to technical and non-technical stakeholders. Desirable Requirements: Experience applying semantic technologies in pharmaceutical, healthcare, life sciences, commercial, clinical, medical, real-world data, or another regulated data environment. Experience supporting generative AI, agentic AI, LLM-powered products, RAG/GraphRAG, vector databases, graph-enhanced retrieval, knowledge graph embeddings, enterprise search, or AI-ready semantic layers. Familiarity with FAIR data principles, master/reference data modernization, metadata platform roadmaps, ontology governance forums, stewardship operating models, and enterprise knowledge architecture practices. Experience with cloud-based data and AI ecosystems, graph/vector tooling, semantic layer technologies, API-based semantic services, and integration with enterprise search or analytics platforms. Experience mentoring junior semantic/knowledge engineers, shaping reusable engineering patterns, and contributing to technical standards or communities of practice. Advanced degree or relevant certification in Computer Science, Information Science, Data Science, Artificial Intelligence, Bioinformatics, Knowledge Engineering, Ontology Engineering, or a related discipline. Novartis Compensation Summary: The salary for this position is expected to range between $176,400 and $327,600 per year. The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors. Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards. US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together? Benefits and Rewards: Learn about all the ways we'll help you thrive personally and professionally. Read our handbook (PDF 30 MB) EEO Statement: The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. Accessibility & Reasonable Accommodations The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to email protected or call + and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
AI Engineer 4 (AI Foundations)
Capital One New York, New York
AI Engineer 4 (AI Foundations) 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/23/2026
Full time
AI Engineer 4 (AI Foundations) 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. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Foundations, VLM Customization)
Capital One Mc Lean, Virginia
AI Engineer 4 (AI Foundations, VLM Customization) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/22/2026
Full time
AI Engineer 4 (AI Foundations, VLM Customization) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (AI Foundations, VLM Customization)
Capital One New York, New York
AI Engineer 4 (AI Foundations, VLM Customization) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/22/2026
Full time
AI Engineer 4 (AI Foundations, VLM Customization) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Applied AI Engineer
Blossom Health New York, New York
Job Description Job Description Blossom Health exists to solve the mental health epidemic in America by partnering with psychiatrists to expand access to affordable, timely, clinically-effective mental healthcare. Our AI-native care platform is loved by hundreds of clinicians and thousands of patients. We're a Series A company with $20M+ raised from Headline, Village Global, and the founders of General Catalyst, Flatiron Health, Sword Health, Grow Therapy, Fay, Elemy, Zip, Blank Street, Assured, Bridge, Birches Health, and Enzo Health. Why you should work here: Hyper-growth environment: Get firsthand exposure to how a startup scales from 0 1 n, with visibility across product, engineering, and operations High trust and autonomy: You'll own meaningful projects from day one and shape both technical decisions and product direction. We trust engineers to figure out the best path forward - without micromanagement. Talent-dense team: Work with a top-percentile team built on mutual respect and admiration, with shared goals, motivations, and vision for the future. Real impact: Your code will directly improve access to mental health care for thousands of patients and clinicians What we're looking for: Highly motivated, ambitious, and capable - looking to tackle a large, meaningful problem area Ownership mindset - thinking for the long-term and placing the business and our customers first High velocity and high excellence - have a real sense of urgency to move quickly and take pride in the quality of your work An explorer - comfortable with ambiguity and autonomy, seeking to answer questions previously unasked, to leap into the unknown An optimist - you believe in a tomorrow better than today A builder - you take joy in bringing new creation to the world, in leveraging technology to make useful things Humble - you use your gifts in the service of others and understand that success is an output, not an input What you'll do: Build and ship AI-native product experiences used directly by clinicians and patients Design and develop LLM-powered systems and agents that automate and augment complex healthcare workflows Own AI features end-to-end, from prototyping and experimentation through production deployment, evaluation, and iteration Build robust evaluation, monitoring, and feedback systems to continuously improve AI quality, reliability, and performance Work across models, prompts, tools, retrieval systems, and application infrastructure to solve real-world product problems Move quickly from emerging AI capabilities to production-ready experiences that deliver measurable value Collaborate closely with clinicians and engineers to understand complex healthcare workflows and determine where AI can have the greatest impact You'll thrive here if you: Have a bachelor's degree or equivalent experience in Computer Science or a related field Have 2+ years of professional software engineering experience outperforming in high-quality environments Have experience building and shipping LLM-powered applications or AI products in production Are fluent in Python and/or TypeScript Have worked with modern LLM APIs, agentic systems, tool calling, retrieval, structured outputs, or similar applied AI patterns Think rigorously about evals, reliability, latency, cost, and failure modes , not just whether a prototype works Are comfortable moving across the stack and quickly experimenting with new models, frameworks, and techniques Love autonomy, ambiguity, experimentation, and ownership Are authorized to work in the U.S. and excited to be in-person in NYC 5 days a week Benefits: Competitive salary, equity, growth opportunities Best-in-class health, dental, and vision insurance A focus on outcomes, not hours, with unlimited PTO Team outings, offsites, and a sunny NYC office stocked with snacks Compensation Range: $150K - $220K
10/22/2026
Full time
Job Description Job Description Blossom Health exists to solve the mental health epidemic in America by partnering with psychiatrists to expand access to affordable, timely, clinically-effective mental healthcare. Our AI-native care platform is loved by hundreds of clinicians and thousands of patients. We're a Series A company with $20M+ raised from Headline, Village Global, and the founders of General Catalyst, Flatiron Health, Sword Health, Grow Therapy, Fay, Elemy, Zip, Blank Street, Assured, Bridge, Birches Health, and Enzo Health. Why you should work here: Hyper-growth environment: Get firsthand exposure to how a startup scales from 0 1 n, with visibility across product, engineering, and operations High trust and autonomy: You'll own meaningful projects from day one and shape both technical decisions and product direction. We trust engineers to figure out the best path forward - without micromanagement. Talent-dense team: Work with a top-percentile team built on mutual respect and admiration, with shared goals, motivations, and vision for the future. Real impact: Your code will directly improve access to mental health care for thousands of patients and clinicians What we're looking for: Highly motivated, ambitious, and capable - looking to tackle a large, meaningful problem area Ownership mindset - thinking for the long-term and placing the business and our customers first High velocity and high excellence - have a real sense of urgency to move quickly and take pride in the quality of your work An explorer - comfortable with ambiguity and autonomy, seeking to answer questions previously unasked, to leap into the unknown An optimist - you believe in a tomorrow better than today A builder - you take joy in bringing new creation to the world, in leveraging technology to make useful things Humble - you use your gifts in the service of others and understand that success is an output, not an input What you'll do: Build and ship AI-native product experiences used directly by clinicians and patients Design and develop LLM-powered systems and agents that automate and augment complex healthcare workflows Own AI features end-to-end, from prototyping and experimentation through production deployment, evaluation, and iteration Build robust evaluation, monitoring, and feedback systems to continuously improve AI quality, reliability, and performance Work across models, prompts, tools, retrieval systems, and application infrastructure to solve real-world product problems Move quickly from emerging AI capabilities to production-ready experiences that deliver measurable value Collaborate closely with clinicians and engineers to understand complex healthcare workflows and determine where AI can have the greatest impact You'll thrive here if you: Have a bachelor's degree or equivalent experience in Computer Science or a related field Have 2+ years of professional software engineering experience outperforming in high-quality environments Have experience building and shipping LLM-powered applications or AI products in production Are fluent in Python and/or TypeScript Have worked with modern LLM APIs, agentic systems, tool calling, retrieval, structured outputs, or similar applied AI patterns Think rigorously about evals, reliability, latency, cost, and failure modes , not just whether a prototype works Are comfortable moving across the stack and quickly experimenting with new models, frameworks, and techniques Love autonomy, ambiguity, experimentation, and ownership Are authorized to work in the U.S. and excited to be in-person in NYC 5 days a week Benefits: Competitive salary, equity, growth opportunities Best-in-class health, dental, and vision insurance A focus on outcomes, not hours, with unlimited PTO Team outings, offsites, and a sunny NYC office stocked with snacks Compensation Range: $150K - $220K
Applied AI Lead Developer
Family Dollar Chesapeake, Virginia
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar
10/22/2026
Full time
Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar
AI Engineer 5 (AI Foundations)
Capital One Mc Lean, Virginia
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. 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
10/20/2026
Full time
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. 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 Deployment Strategist
Pigment San Francisco, California
Job Description Job Description Join Pigment: The AI Platform Redefining Business Planning Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team-from Finance to HR-to build, adapt, and align strategic plans in real time. Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario. With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner Magic Quadrant for Financial Planning Software. At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo-all while working as one team. If you're driven by innovation and ready to make an impact at scale, we'd love to hear from you. What you'll do We are looking for an AI Deployment Strategist to join our growing team. In this role, you will work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment. This is a highly cross-functional role at the intersection of engineering, data, and business problem-solving. You will own the end-to-end implementation of Pigment's AI capabilities for strategic customers - from translating business problems into models, to deploying agentic AI solutions in production. You will play a key role in shaping how organizations leverage Pigment to transform their planning processes, while acting as a critical feedback loop between customers and our Product and Engineering teams. What you'll work onBuild & deploy AI-powered solutions Translate complex business problems into scalable Pigment models using AI agents, formulas, dimensions, and advanced logic Design, build, and deploy custom AI agents tailored to customer workflows and decision-making processes Own end-to-end implementation of Pigment for key customers Work directly with customers Partner with business and technical stakeholders to rethink processes and design AI-driven solutions Act as a trusted advisor, guiding customers on best practices Drive adoption and ensure customers maximize value from Pigment Prototype & innovate Develop prototypes and experimental AI use cases to solve emerging customer needs Test and iterate on new approaches to agent-based planning and automation Bridge product, engineering, and customers Collaborate closely with Customer Success, Solutions Architects, and Product teams Translate customer feedback into clear product requirements and specifications Contribute to the evolution of Pigment's AI capabilities Enable and scale Train users and teams on Pigment features, modeling best practices, and scalable system design Help define repeatable patterns and frameworks for AI deployments across customers What we're looking forRequired Engineering or computer science degree from top tier institution 2-5 years in a technical, client-facing, or implementation role, such as: Forward Deployed Engineer Data Scientist / AI Engineer Solutions Architect / Solutions Engineer Technical or Implementation Consultant Strong analytical and problem-solving skills with experience in: Data modeling, analytics, or business logic design AI / ML concepts or applied data workflows Proficiency with: Formulas, logic, and structured modeling Programming (Python, SQL, or similar is a plus) Familiarity with: SaaS platforms or planning tools APIs, data pipelines, and system integration concepts Ability to manage multiple stakeholders and projects in fast-paced environments Nice to have Background in FP&A, financial modeling, or business planning workflows Prior experience with Pigment or similar platforms Additional European language(s) outside of English What success looks like Customers successfully deploy and adopt AI-powered planning workflows Innovative agentic AI solutions are built and scaled across use cases You are seen as a trusted technical partner by customers Strong feedback loops drive continuous product improvement Repeatable patterns emerge to scale AI deployments across Pigment customers We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice . We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
10/20/2026
Full time
Job Description Job Description Join Pigment: The AI Platform Redefining Business Planning Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team-from Finance to HR-to build, adapt, and align strategic plans in real time. Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario. With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner Magic Quadrant for Financial Planning Software. At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo-all while working as one team. If you're driven by innovation and ready to make an impact at scale, we'd love to hear from you. What you'll do We are looking for an AI Deployment Strategist to join our growing team. In this role, you will work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment. This is a highly cross-functional role at the intersection of engineering, data, and business problem-solving. You will own the end-to-end implementation of Pigment's AI capabilities for strategic customers - from translating business problems into models, to deploying agentic AI solutions in production. You will play a key role in shaping how organizations leverage Pigment to transform their planning processes, while acting as a critical feedback loop between customers and our Product and Engineering teams. What you'll work onBuild & deploy AI-powered solutions Translate complex business problems into scalable Pigment models using AI agents, formulas, dimensions, and advanced logic Design, build, and deploy custom AI agents tailored to customer workflows and decision-making processes Own end-to-end implementation of Pigment for key customers Work directly with customers Partner with business and technical stakeholders to rethink processes and design AI-driven solutions Act as a trusted advisor, guiding customers on best practices Drive adoption and ensure customers maximize value from Pigment Prototype & innovate Develop prototypes and experimental AI use cases to solve emerging customer needs Test and iterate on new approaches to agent-based planning and automation Bridge product, engineering, and customers Collaborate closely with Customer Success, Solutions Architects, and Product teams Translate customer feedback into clear product requirements and specifications Contribute to the evolution of Pigment's AI capabilities Enable and scale Train users and teams on Pigment features, modeling best practices, and scalable system design Help define repeatable patterns and frameworks for AI deployments across customers What we're looking forRequired Engineering or computer science degree from top tier institution 2-5 years in a technical, client-facing, or implementation role, such as: Forward Deployed Engineer Data Scientist / AI Engineer Solutions Architect / Solutions Engineer Technical or Implementation Consultant Strong analytical and problem-solving skills with experience in: Data modeling, analytics, or business logic design AI / ML concepts or applied data workflows Proficiency with: Formulas, logic, and structured modeling Programming (Python, SQL, or similar is a plus) Familiarity with: SaaS platforms or planning tools APIs, data pipelines, and system integration concepts Ability to manage multiple stakeholders and projects in fast-paced environments Nice to have Background in FP&A, financial modeling, or business planning workflows Prior experience with Pigment or similar platforms Additional European language(s) outside of English What success looks like Customers successfully deploy and adopt AI-powered planning workflows Innovative agentic AI solutions are built and scaled across use cases You are seen as a trusted technical partner by customers Strong feedback loops drive continuous product improvement Repeatable patterns emerge to scale AI deployments across Pigment customers We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice . We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
AI Deployment Strategist
Pigment Bellville, Texas
Job Description Job Description Join Pigment: The AI Platform Redefining Business Planning Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team-from Finance to HR-to build, adapt, and align strategic plans in real time. Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario. With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner Magic Quadrant for Financial Planning Software. At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo-all while working as one team. If you're driven by innovation and ready to make an impact at scale, we'd love to hear from you. What you'll do We are looking for an AI Deployment Strategist to join our growing team. In this role, you will work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment. This is a highly cross-functional role at the intersection of engineering, data, and business problem-solving. You will own the end-to-end implementation of Pigment's AI capabilities for strategic customers - from translating business problems into models, to deploying agentic AI solutions in production. You will play a key role in shaping how organizations leverage Pigment to transform their planning processes, while acting as a critical feedback loop between customers and our Product and Engineering teams. What you'll work onBuild & deploy AI-powered solutions Translate complex business problems into scalable Pigment models using AI agents, formulas, dimensions, and advanced logic Design, build, and deploy custom AI agents tailored to customer workflows and decision-making processes Own end-to-end implementation of Pigment for key customers Work directly with customers Partner with business and technical stakeholders to rethink processes and design AI-driven solutions Act as a trusted advisor, guiding customers on best practices Drive adoption and ensure customers maximize value from Pigment Prototype & innovate Develop prototypes and experimental AI use cases to solve emerging customer needs Test and iterate on new approaches to agent-based planning and automation Bridge product, engineering, and customers Collaborate closely with Customer Success, Solutions Architects, and Product teams Translate customer feedback into clear product requirements and specifications Contribute to the evolution of Pigment's AI capabilities Enable and scale Train users and teams on Pigment features, modeling best practices, and scalable system design Help define repeatable patterns and frameworks for AI deployments across customers What we're looking forRequired Engineering or computer science degree from top tier institution 2-5 years in a technical, client-facing, or implementation role, such as: Forward Deployed Engineer Data Scientist / AI Engineer Solutions Architect / Solutions Engineer Technical or Implementation Consultant Strong analytical and problem-solving skills with experience in: Data modeling, analytics, or business logic design AI / ML concepts or applied data workflows Proficiency with: Formulas, logic, and structured modeling Programming (Python, SQL, or similar is a plus) Familiarity with: SaaS platforms or planning tools APIs, data pipelines, and system integration concepts Ability to manage multiple stakeholders and projects in fast-paced environments Nice to have Background in FP&A, financial modeling, or business planning workflows Prior experience with Pigment or similar platforms Additional European language(s) outside of English What success looks like Customers successfully deploy and adopt AI-powered planning workflows Innovative agentic AI solutions are built and scaled across use cases You are seen as a trusted technical partner by customers Strong feedback loops drive continuous product improvement Repeatable patterns emerge to scale AI deployments across Pigment customers We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice . We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
10/20/2026
Full time
Job Description Job Description Join Pigment: The AI Platform Redefining Business Planning Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team-from Finance to HR-to build, adapt, and align strategic plans in real time. Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario. With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner Magic Quadrant for Financial Planning Software. At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo-all while working as one team. If you're driven by innovation and ready to make an impact at scale, we'd love to hear from you. What you'll do We are looking for an AI Deployment Strategist to join our growing team. In this role, you will work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment. This is a highly cross-functional role at the intersection of engineering, data, and business problem-solving. You will own the end-to-end implementation of Pigment's AI capabilities for strategic customers - from translating business problems into models, to deploying agentic AI solutions in production. You will play a key role in shaping how organizations leverage Pigment to transform their planning processes, while acting as a critical feedback loop between customers and our Product and Engineering teams. What you'll work onBuild & deploy AI-powered solutions Translate complex business problems into scalable Pigment models using AI agents, formulas, dimensions, and advanced logic Design, build, and deploy custom AI agents tailored to customer workflows and decision-making processes Own end-to-end implementation of Pigment for key customers Work directly with customers Partner with business and technical stakeholders to rethink processes and design AI-driven solutions Act as a trusted advisor, guiding customers on best practices Drive adoption and ensure customers maximize value from Pigment Prototype & innovate Develop prototypes and experimental AI use cases to solve emerging customer needs Test and iterate on new approaches to agent-based planning and automation Bridge product, engineering, and customers Collaborate closely with Customer Success, Solutions Architects, and Product teams Translate customer feedback into clear product requirements and specifications Contribute to the evolution of Pigment's AI capabilities Enable and scale Train users and teams on Pigment features, modeling best practices, and scalable system design Help define repeatable patterns and frameworks for AI deployments across customers What we're looking forRequired Engineering or computer science degree from top tier institution 2-5 years in a technical, client-facing, or implementation role, such as: Forward Deployed Engineer Data Scientist / AI Engineer Solutions Architect / Solutions Engineer Technical or Implementation Consultant Strong analytical and problem-solving skills with experience in: Data modeling, analytics, or business logic design AI / ML concepts or applied data workflows Proficiency with: Formulas, logic, and structured modeling Programming (Python, SQL, or similar is a plus) Familiarity with: SaaS platforms or planning tools APIs, data pipelines, and system integration concepts Ability to manage multiple stakeholders and projects in fast-paced environments Nice to have Background in FP&A, financial modeling, or business planning workflows Prior experience with Pigment or similar platforms Additional European language(s) outside of English What success looks like Customers successfully deploy and adopt AI-powered planning workflows Innovative agentic AI solutions are built and scaled across use cases You are seen as a trusted technical partner by customers Strong feedback loops drive continuous product improvement Repeatable patterns emerge to scale AI deployments across Pigment customers We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice . We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
QA AI Automation Engineer
Dynasty Financial Partners, LLC Saint Petersburg, Florida
Job Description Job Description Description: About the Role We are building AI systems that advisors and their clients rely on inside a regulated wealth management platform - an internal AI assistant, an external-facing API layer on top of it, and a growing set of agentic workflows. The bar for correctness, grounding, and auditability is higher here than it is for most AI products. This role exists because traditional QA does not cover that surface. We need an engineer who can evaluate non-deterministic systems, build the tooling that catches AI regressions before they reach an advisor, and hold the line on code quality now that a meaningful share of our code is written by autonomous coding agents. This is a hands-on engineering role, not a test-execution role. What You'll Do 1. Own and extend our AI evaluation framework for AI chat Build and maintain evaluation suite for our AI assistant and its API surface - correctness, grounding/citation fidelity, retrieval quality, refusal and escalation behavior, tone, latency, and cost per interaction. Curate and version golden datasets and adversarial test sets drawn from real advisor workflows; keep them representative as the product changes. Design LLM-as-judge and rubric-based scoring where deterministic assertions do not apply and validate the judges themselves against human-labeled sets. Wire evals into CI so prompt, model, retrieval, and tool changes are gated by measured regression - not by vibes. Instrument production traces and close the loop from live failures back into the eval suite. 2. Build the multi-agent AI quality step that finds defects automatically Design and operate a multi-agent workflow in our CI/CD pipeline that runs on commit: executes the suite, triages failures, writes up defects with reproduction detail, proposes or applies fixes, and re-runs to verify. Define agent roles, hand-off logic, guardrails, and the quality checks that decide when an agent's output is trustworthy enough to auto-apply versus route to a human. Make cost-aware calls on where an LLM us needed and where deterministic automation is simply the better tool. Report on the loop's real impact - autonomous resolution rate, false-positive rate, engineer hours returned. 3. Scale code quality in the age of autonomous agent coding Define what "good" means for agent-authored code and build the automated gates that enforce it: coverage and mutation testing, static analysis, security and dependency scanning, architectural conformance, and review checklists tuned to how agents fail. Identify the failure modes specific to agent-generated code - plausible-but-wrong logic, silent scope creep, duplicated abstractions, missing edge-case handling, tests written to pass rather than to verify - and build detection for them. Partner with architects and delivery teams to keep velocity from outrunning quality as agent-assisted development scales across the org. Across all three Partner with product, engineering, and AI Labs to define coverage and acceptance criteria for AI features before they are built. Contribute to release-readiness and go/no-go decisions with evidence. Maintain and modernize our existing automation estate (API, UI, integration) and mentor engineers on Requirements: Required 5+ years in software quality, test automation, or SDET work, with real ownership of automation architecture - not just test authoring. Demonstrated production experience with LLM-powered systems: agent patterns, prompt engineering, tool/function calling, and orchestration. Hands-on with major model APIs (OpenAI, Anthropic, Azure OpenAI) and AI-assisted development tooling (Claude Code, Copilot, Codex or equivalent). Strong programming in at least one of Python, TypeScript/JavaScript, Java, Kotlin, or C#, and comfort reading across the others. Experience building and interpreting evaluation criteria for systems without a single correct answer. Deep CI/CD fluency - pipeline integration, gating, monitoring, and logging. API testing depth and experience validating third-party integrations. Clear written communication; you can explain a quality risk to a product owner and a root cause to an engineer in the same day. Preferred Eval and observability tooling: Langfuse, Promptfoo, OpenTelemetry, New Relic, or equivalents. RAG fundamentals - embeddings, chunking strategy, vector search, retrieval evaluation. Workflow orchestration tooling (n8n or similar). Azure cloud services; .NET ecosystem exposure. BDD/Selenium or comparable UI automation at scale. Financial services, wealth management, or another regulated domain - or a clear appetite for what data governance means in one. Experience mentoring or leading distributed QA engineers. First 90 Days Days 1-30: Learn the assistant, the API layer, and the current eval and automation estate. Ship a baseline eval suite for one high-traffic chat workflow with results visible in CI. Days 31-60: Stand up the first multi-agent defect-detection step on a single service; establish the trust threshold for auto-applied fixes and publish the metrics. Days 61-90: Propose and begin rolling out the agent-authored code quality standard across delivery teams, with automated gates.
10/19/2026
Full time
Job Description Job Description Description: About the Role We are building AI systems that advisors and their clients rely on inside a regulated wealth management platform - an internal AI assistant, an external-facing API layer on top of it, and a growing set of agentic workflows. The bar for correctness, grounding, and auditability is higher here than it is for most AI products. This role exists because traditional QA does not cover that surface. We need an engineer who can evaluate non-deterministic systems, build the tooling that catches AI regressions before they reach an advisor, and hold the line on code quality now that a meaningful share of our code is written by autonomous coding agents. This is a hands-on engineering role, not a test-execution role. What You'll Do 1. Own and extend our AI evaluation framework for AI chat Build and maintain evaluation suite for our AI assistant and its API surface - correctness, grounding/citation fidelity, retrieval quality, refusal and escalation behavior, tone, latency, and cost per interaction. Curate and version golden datasets and adversarial test sets drawn from real advisor workflows; keep them representative as the product changes. Design LLM-as-judge and rubric-based scoring where deterministic assertions do not apply and validate the judges themselves against human-labeled sets. Wire evals into CI so prompt, model, retrieval, and tool changes are gated by measured regression - not by vibes. Instrument production traces and close the loop from live failures back into the eval suite. 2. Build the multi-agent AI quality step that finds defects automatically Design and operate a multi-agent workflow in our CI/CD pipeline that runs on commit: executes the suite, triages failures, writes up defects with reproduction detail, proposes or applies fixes, and re-runs to verify. Define agent roles, hand-off logic, guardrails, and the quality checks that decide when an agent's output is trustworthy enough to auto-apply versus route to a human. Make cost-aware calls on where an LLM us needed and where deterministic automation is simply the better tool. Report on the loop's real impact - autonomous resolution rate, false-positive rate, engineer hours returned. 3. Scale code quality in the age of autonomous agent coding Define what "good" means for agent-authored code and build the automated gates that enforce it: coverage and mutation testing, static analysis, security and dependency scanning, architectural conformance, and review checklists tuned to how agents fail. Identify the failure modes specific to agent-generated code - plausible-but-wrong logic, silent scope creep, duplicated abstractions, missing edge-case handling, tests written to pass rather than to verify - and build detection for them. Partner with architects and delivery teams to keep velocity from outrunning quality as agent-assisted development scales across the org. Across all three Partner with product, engineering, and AI Labs to define coverage and acceptance criteria for AI features before they are built. Contribute to release-readiness and go/no-go decisions with evidence. Maintain and modernize our existing automation estate (API, UI, integration) and mentor engineers on Requirements: Required 5+ years in software quality, test automation, or SDET work, with real ownership of automation architecture - not just test authoring. Demonstrated production experience with LLM-powered systems: agent patterns, prompt engineering, tool/function calling, and orchestration. Hands-on with major model APIs (OpenAI, Anthropic, Azure OpenAI) and AI-assisted development tooling (Claude Code, Copilot, Codex or equivalent). Strong programming in at least one of Python, TypeScript/JavaScript, Java, Kotlin, or C#, and comfort reading across the others. Experience building and interpreting evaluation criteria for systems without a single correct answer. Deep CI/CD fluency - pipeline integration, gating, monitoring, and logging. API testing depth and experience validating third-party integrations. Clear written communication; you can explain a quality risk to a product owner and a root cause to an engineer in the same day. Preferred Eval and observability tooling: Langfuse, Promptfoo, OpenTelemetry, New Relic, or equivalents. RAG fundamentals - embeddings, chunking strategy, vector search, retrieval evaluation. Workflow orchestration tooling (n8n or similar). Azure cloud services; .NET ecosystem exposure. BDD/Selenium or comparable UI automation at scale. Financial services, wealth management, or another regulated domain - or a clear appetite for what data governance means in one. Experience mentoring or leading distributed QA engineers. First 90 Days Days 1-30: Learn the assistant, the API layer, and the current eval and automation estate. Ship a baseline eval suite for one high-traffic chat workflow with results visible in CI. Days 31-60: Stand up the first multi-agent defect-detection step on a single service; establish the trust threshold for auto-applied fixes and publish the metrics. Days 61-90: Propose and begin rolling out the agent-authored code quality standard across delivery teams, with automated gates.
Applied AI Engineer
Material Bank Raleigh, North Carolina
Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.
10/19/2026
Full time
Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.
Applied AI Engineer
Material Bank Boca Raton, Florida
Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.
10/19/2026
Full time
Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.
Applied AI Engineer
Material Bank Boston, Massachusetts
Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.
10/19/2026
Full time
Job Description Job Description Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials. About the role As an Applied AI Engineer, you will drive the design, build, and deployment of next-generation AI-powered experiences across Material Bank's platform. You will work as part of the team responsible for taking ideas from concept to production - building intelligent systems and user experiences that blend cutting-edge AI capabilities with the high standards of quality, aesthetics, and usability expected in the architecture and community. This is a senior-level individual contributor role focused on applied AI product development. You will work across the stack to architect and deploy scalable AI systems that enhance how users discover, understand, and engage with products, materials, and creative content. Your work will span areas such as multimodal search and understanding, AI-assisted content generation, intelligent workflows, personalization, creative tooling, and agentic systems. We are looking for someone who not only understands modern AI systems technically, but also has strong product instincts, visual sensibility, and genuine passion for building AI experiences that feel thoughtful, polished, and useful. AI will play a foundational role in the future of Material Bank's platform, and you will help define and build that future. What you'll do Design, build, and deploy end-to-end AI-powered product experiences from concept through production. Architect and implement scalable AI systems leveraging LLMs, embeddings, multimodal models, retrieval systems, agent frameworks, and modern data infrastructure. Build production-grade multi-agent workflows and orchestration systems using frameworks such as LangGraph, LangChain, Mastra, and custom tooling. Develop and optimize Retrieval-Augmented Generation (RAG) systems, including embeddings, vector search, retrieval pipelines, chunking strategies, and relevance tuning. Build multimodal AI workflows that analyze and reason over images, creative assets, and visual datasets using modern multimodal LLMs, embedding models, and specialized tooling such as SAM2/SAM3. Create AI-assisted experiences for search, discovery, content generation, personalization, and creative workflows across Material Bank's platform. Evaluate, refine, and improve AI-generated outputs for quality, tone, accuracy, and creative alignment through testing, iteration, and human-in-the-loop evaluation strategies. Partner closely with Product, Design, Engineering, Data, and Executive Leadership to identify high-impact opportunities and translate ambiguous ideas into production-ready AI capabilities. Make architectural decisions that balance speed, scalability, latency, cost, accuracy, and long-term maintainability. Continuously evaluate emerging AI technologies, models, frameworks, and workflows to identify opportunities that create meaningful business and user value. What you'll bring 8+ years of experience building and shipping production software, including significant full-stack engineering experience. Demonstrated success designing and deploying production-grade AI/ML systems and AI-powered product experiences. Deep hands-on experience with LLMs, embeddings, multimodal AI systems, RAG architectures, and multi-agent frameworks such as LangGraph, LangChain, Mastra, or equivalent custom tooling. Strong engineering fundamentals across backend systems, APIs, data pipelines, cloud infrastructure, and modern JavaScript/TypeScript and Python ecosystems. Experience working with multimodal models, visual analysis systems, and image-based AI workflows at scale, including familiarity with modern image-generation tooling and services. Strong systems thinking with the ability to balance trade-offs across latency, cost, scalability, accuracy, reliability, and user experience. Proven ability to independently take ambiguous problems from idea to shipped product with minimal oversight. Strong product instincts, visual sensibility, and a high bar for quality, usability, and craftsmanship in AI-generated experiences. Genuine interest in creative industries such as architecture, design, fashion, media, photography, or art, with an appreciation for aesthetics and taste. Open-source contributions, side projects, or publicly demonstrable AI work that reflects curiosity, experimentation, and passion for applied AI are strongly preferred. Strong communication and collaboration skills, with the ability to work effectively across both technical and non-technical teams. What you'll get from us: Our people : We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution. Relaxation and Celebrations : Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect). Health Benefits : We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program. Plan for your Retirement : 401(k) eligible after your first 90 day's employed! Giving Back : We sponsor multiple events throughout the year to help out our communities. Growth : We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters! Flexible Work Schedules : With business units and employees across the globe, Material Technologies has embraced a hybrid working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both. Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.
AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI)
Capital One New York, New York
AI Engineer 5 AI Foundations, LLM Core and 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. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
10/19/2026
Full time
AI Engineer 5 AI Foundations, LLM Core and 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. Please note that any position posted in Canada is for Capital One Canada . click apply for full job details
AI Engineer 4 (MLX)
Capital One New York, New York
AI Engineer 4 (MLX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/19/2026
Full time
AI Engineer 4 (MLX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (MLX)
Capital One Mc Lean, Virginia
AI Engineer 4 (MLX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/19/2026
Full time
AI Engineer 4 (MLX) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Francisco, CA: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
AI Engineer 4 (Vision model (VLM) customization experience)
Capital One Mc Lean, Virginia
AI Engineer 4 (Vision model (VLM) customization experience) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
10/19/2026
Full time
AI Engineer 4 (Vision model (VLM) customization experience) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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