Sr. Staff AI Engineer

The Sr. Staff AI Engineer role at Capital One focuses on designing and delivering responsible, reliable AI platform capabilities that support both internal associate workflows and customer experiences.

Role Overview

You will help build scalable AI software components spanning foundation model training and large language model inference, along with agents and multi-agent workflows. The work also includes model evaluation, governance, and observability to support safe and dependable deployment.

Onsite Location

McLean, VA (onsite)

Compensation

USD 314,800 - 359,300 per year

• Cambridge, MA: $314,800 - $359,300
• McLean, VA: $314,800 - $359,300
• New York, NY: $343,400 - $392,000
• Richmond, VA: $286,200 - $326,700
• San Francisco, CA: $343,400 - $392,000
• San Jose, CA: $343,400 - $392,000

Responsibilities

• Partner with cross-functional teams including engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
• Design, develop, test, deploy, and support AI software components across foundation model training, LLM 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 advanced foundation model optimization techniques to improve scalability, cost, latency, and throughput in large-scale production systems.
• Contribute to the technical vision and long-term roadmap for foundational AI systems within Capital One.
• Define and guide technical AI architecture by integrating applied research breakthroughs into production ecosystems with reliability and scale.
• Establish AI performance, safety, and transparency standards that guide model development and deployment company-wide.
• Lead 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 to develop the next generation of AI technical leadership.

Required Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 10 years of experience developing AI and ML algorithms or technologies; or a Master’s degree in a related field plus at least 8 years of experience developing AI and ML algorithms or technologies.
• At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java.

Preferred Qualifications

• Experience architecting AI platforms with tradeoff decisions across cost, latency, throughput, and accuracy.
• 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., 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 (including LLM inference, similarity search and VectorDBs, guardrails, and 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 building agentic AI systems and agentic workflows.
• 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.
• 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 for requirements such as context length, token inputs, and token outputs.

Technology Stack

• AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
• Python, Go, Scala, CUDA, Java
• AWS, Google Cloud, Azure
• C++, C#, Golang

Benefits

Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits supporting your total well-being.

Incentive Compensation

• Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).
• Eligibility depends on full-time or part-time status, exempt or non-exempt status, and management level.

Additional Information

• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
• Applications are expected to be accepted 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, or guarantee third-party products, services, educational tools, or other information available through this site, and is not liable for them.