Capital One is hiring a Sr. Staff AI Engineer in McLean, VA (onsite) to help build responsible, reliable AI systems. In this role, you will partner across engineering and product teams to design and deploy scalable AI platform capabilities, spanning foundation model training, LLM inference, agent and workflow systems, evaluation, governance, and observability.
What you’ll do
- Collaborate with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how associates work and how customers interact with Capital One.
- Design, develop, test, deploy, and support AI software components across the full lifecycle, 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.
- Introduce state-of-the-art foundation model optimization techniques to improve performance, including scalability, cost, latency, and throughput.
- Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
- Define and guide the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale.
- Lead the establishment of AI performance, safety, and transparency standards that guide model development and deployment company-wide.
- Drive multi-year platform initiatives that unify data, compute, and model lifecycle management within a cohesive enterprise AI architecture.
- Mentor senior technical leaders across research, data, and engineering disciplines to develop the next generation of Capital One AI technical leadership.
Required qualifications
- Bachelor’s Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies; or Master’s Degree plus at least 8 years.
- At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java.
Preferred qualifications
- Experience architecting AI platforms with tradeoffs across cost, latency, throughput, and accuracy.
- 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (for example, AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
- Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level.
- Experience developing AI and ML algorithms or technologies (for example, LLM inference, similarity search and VectorDBs, guardrails, memory) using Python, C++, C#, Java, CUDA, or Golang.
- Experience developing and applying state-of-the-art training and inference optimization techniques to improve hardware utilization, latency, throughput, and cost.
- Experience building agentic AI systems and agentic workflows.
- Passion for staying current with AI research and applying novel techniques judiciously in production.
- Excellent communication and presentation skills, including the ability to articulate complex AI concepts to peers.
- Recognition as an industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership.
- Demonstrated experience designing long-term AI infrastructure strategies, balancing cost, scale, ethics, and regulatory compliance.
- Experience driving organization-wide adoption of AI safety, alignment, and governance standards in collaboration with policy, risk, and legal teams.
- Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact.
- Experience right-sizing models, instance counts, and hardware types based on requirements (for example, context length, token inputs, token outputs).
Technologies
- AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
- Python, Go, Scala, CUDA, Java
- AWS, Google Cloud, Azure
- C++, C#, Golang
Compensation and benefits
Salary: $314,800 - $359,300 per year (McLean, VA, onsite).
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits to support your total well-being.
Incentive compensation: This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
Additional details
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
- 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 does not provide, endorse nor guarantee, and is not liable for third-party products, services, educational tools, or other information available through this site.
