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

Capital One is building responsible, scalable AI capabilities through its Intelligent Foundations and Experiences (IFX) team, supporting how associates work and how customers interact with the company. This AI Engineer 5 role helps design, deploy, and operate AI-powered products spanning foundation model training, LLM inference, and agentic workflows, with a strong focus on orchestration, evaluation, guardrails, and governance.

What you’ll do

• Work with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for internal and customer-facing impact.
• 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.
• Use a broad mix of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
• Develop and introduce foundation model optimization techniques to improve production performance across scalability, cost, latency, and throughput.
• Help shape the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Build and optimize multi-model orchestration pipelines that integrate LLMs, vector search, and domain-specific models into unified systems.
• Lead cost-performance governance reviews across AI systems, including tracking GPU utilization, model throughput, and inference cost efficiency.
• Participate in or lead team design councils or design review boards to maintain technical consistency and compliance with AI engineering standards.
• Mentor Principal and Manager-level AI engineers to drive cross-domain learning and raise organizational technical maturity.

What you’ll bring

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

Tools and 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, Generative components, Rule-based, GPU utilization

Compensation and location

This role is based in New York, NY (onsite). Salary range: USD 250,800 - 286,200 per year.

Additional details

• Capital One may consider sponsoring a new qualified applicant for employment authorization.
• Applications are expected to be accepted for a minimum of 5 business days.
• No agencies please.
• Capital One is an equal opportunity employer (EOE), committed to non-discrimination.
• Capital One promotes a drug-free workplace.
• Qualified applicants with a criminal history will be considered consistent with applicable laws.
• If you need an accommodation, contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about the recruiting process, email [email protected].

About the IFX team

The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life. The team works across the company to advance state-of-the-art science and AI engineering, and builds and deploys proprietary solutions central to the business, delivering value to millions of customers through responsible, scalable AI platforms.

Benefits

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

Preferred qualifications

• Experience leading AI systems development with tradeoffs across cost, latency, throughput, and accuracy.
• 7 years deploying scalable and responsible AI solutions on cloud platforms (for example, AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience designing, developing, delivering, and supporting complex AI systems.
• Experience building AI/ML algorithms and technologies such as LLM inference, similarity search, VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang.
• Experience applying state-of-the-art optimization techniques for training and inference software to improve hardware utilization, latency, throughput, and cost.
• Experience building agentic AI systems and agentic workflows.
• Interest in staying current with AI research and applying novel techniques in production.
• Strong communication and presentation skills for explaining complex AI concepts.
• 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.
• Ability to balance model performance and operational cost via dynamic inference strategies and model compression.
• Experience right-sizing models, instance counts, and hardware types based on requirements such as context length, token inputs, and token outputs.