AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI)

Capital One is looking for an AI Engineer 5 to help build and deploy AI-powered products as part of the Intelligent Foundations and Experiences (IFX) team. The role focuses on responsible, scalable AI engineering, spanning foundation model training and LLM and agentic systems, with an emphasis on orchestration, evaluation and guardrails, and cost-performance governance.

This position is based in New York, NY (onsite) and offers a salary range of USD 250,800 - 286,200 per year. A typical candidate has 4+ years of relevant experience, with eligibility also supported via degree-equivalent qualifications.

What you’ll do

• Collaborate with a cross-functional group including engineers, research scientists, technical program managers, and product managers to deliver AI products that improve how associates work and how customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Use a stack of open source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and related tools.
• Develop state-of-the-art foundation model optimization techniques to improve scalability, cost, latency, and throughput for large-scale production AI systems.
• Shape the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Design and optimize multi-model orchestration pipelines that integrate 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 support technical consistency and compliance with AI engineering standards.
• Mentor Principal and Manager-level AI engineers to support cross-domain learning and raise organizational technical maturity.

Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 6 years of experience developing AI and ML algorithms or technologies; or Master’s degree plus at least 4 years of experience developing AI and ML algorithms or technologies.
• At least 6 years of programming experience with Python, Go, Scala, CUDA, or Java.

Technologies

• AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, AWS, Google Cloud, Azure
• Python, Go, Scala, CUDA, Java, C++, C#, Golang
• Vector search, LLMs, foundation model training, retrieval-augmented and generative components, rule-based approaches
• GPU utilization

Team context

The Intelligent Foundations and Experiences (IFX) team is central to delivering Capital One’s AI vision. The team partners across the company to advance the state of the art in science and AI engineering, building and deploying proprietary solutions that support value for millions of customers. AI models and platforms built by the team help other teams enhance products with responsible, scalable AI.

Preferred qualifications

• Experience leading AI systems with tradeoffs across cost, latency, throughput, and accuracy.
• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms such as 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 such as LLM inference, similarity search and VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang.
• Experience applying state-of-the-art techniques to optimize training and inference software for better hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and agentic workflows.
• Strong ability to apply new AI research judiciously in production environments.
• Excellent communication and presentation skills to explain 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 ethical AI deployment standards, 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 such as context length and token input/output needs.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting overall well-being.
• Performance-based incentive compensation eligibility, which may include cash bonuses and/or long-term incentives (LTI).

Additional information

• Capital One may consider sponsoring a new qualified applicant for employment authorization for this position.
• Applications are expected to remain open for a minimum of 5 business days.
• No agencies please.
• Capital One is an equal opportunity employer committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug-free workplace.
• Capital One will consider qualified applicants with a criminal history consistent with applicable laws regarding criminal background inquiries.
• If you require an accommodation, contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about Capital One’s recruiting process, email [email protected].
• Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site.