AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)

Capital One is building responsible GenAI platform services that support scalable, production AI systems, and the Intelligent Foundations and Experiences (IFX) team is at the center of that effort. In this role, you will help design, develop, and optimize AI software components spanning agentic AI, guardrails, and model evaluation, while partnering closely with engineering, research, program, and product stakeholders.

This AI Engineer 5 position is based in McLean, VA and is an onsite role. Salary for this location is USD 229,900 - 262,400 per year.

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 that impact how associates work and how 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.
• Apply a broad stack of open source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch, along with other tools.
• Introduce foundation model optimization techniques to improve scalability, cost, latency, and throughput for large-scale production AI systems.
• Help shape the technical vision and long-term roadmap for foundational AI systems.
• Design, implement, 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 for AI systems, including tracking GPU utilization, model throughput, and inference cost efficiency.
• 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 support cross-domain learning and raise organizational technical maturity.

Qualifications

• Minimum experience: At least 4 years of experience developing AI and ML algorithms or technologies with a Master’s degree; or 6 years with a Bachelor’s degree.
• Education: Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field (or Bachelor’s, as described above).
• Programming experience: At least 6 years programming with Python, Go, Scala, CUDA, or Java.

Technologies

• Python, Go, Scala, CUDA, Java, C++, C#, Golang
• AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, AWS, Google Cloud, Azure
• LLM Inference, Similarity Search, Guardrails, Memory

Team context

• The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life.
• IFX partners across the company to advance science and AI engineering, building and deploying proprietary solutions used by teams and delivering value to millions of customers.
• AI models and platforms enable other teams to enhance products with responsible, scalable AI.

Compensation and incentives

• Base salary (McLean, VA): USD 229,900 - 262,400 per year
• This role is also eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI), depending on the plan.

Benefits and other details

• Comprehensive, competitive, and inclusive health, financial, and other benefits that support total well-being.
• Capital One may consider sponsoring qualified applicants for employment authorization for this position.
• Applications are expected to accept for a minimum of 5 business days.
• No agencies please.
• Capital One is an equal opportunity employer (EOE, including disability/veteran) committed to non-discrimination.
• Capital One promotes a drug-free workplace.
• Capital One is an equal opportunity employer committed to compliance with applicable federal, state, and local laws.

If you need accommodation related to the recruiting process, contact Capital One Recruiting at 1-800-304-9102 or [email protected]. For technical support or questions about the recruiting process, email [email protected].