Staff AI Engineer

The Staff AI Engineer role at Capital One (remote eligible) focuses on building and deploying responsible, scalable AI systems and foundational AI capabilities. The work spans model training and inference, agents, evaluation, governance, observability, and enterprise AI architecture standards.

Location

• McLean, VA (Remote)

Salary Range

• USD 244,700 - 279,200 per year (Remote)
• USD 269,100 - 307,200 per year (McLean, VA)
• USD 269,100 - 307,200 per year (Cambridge, MA)
• USD 293,600 - 335,100 per year (New York, NY)
• USD 293,600 - 335,100 per year (San Francisco, CA)
• USD 293,600 - 335,100 per year (San Jose, CA)

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered at the time of hire will be reflected solely in the candidate’s offer letter.

Role Summary

Build and deploy responsible, scalable AI systems and foundational AI capabilities, including model training and inference, agents, evaluation, governance, observability, and enterprise AI architecture standards.

Responsibilities

• Partner 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 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, PyTorch, and more.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve performance across scalability, cost, latency, and throughput for large scale production AI systems.
• Contribute to the technical vision and long term roadmap of foundational AI systems at Capital One.
• Set technical direction for enterprise-wide AI architecture by unifying tooling, observability, and deployment standards across teams.
• Own design and integration of model routing, caching, and orchestration systems supporting hybrid and multi-model workloads.
• Champion responsible AI principles across system design, embedding transparency, reproducibility, and fairness-by-design.
• Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds.

Required Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master’s degree plus at least 6 years of experience developing AI and ML algorithms or technologies.
• At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java.

Preferred Qualifications

• Experience designing AI systems with tradeoff decisions across cost, latency, throughput, and accuracy.
• 8+ 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 VP level.
• Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search and VectorDBs, guardrails, 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 articulating complex AI concepts to peers.
• Proven track record defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability, and evaluation frameworks.
• Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance, and compute efficiency.
• Demonstrated success influencing research-to-production promotion processes, including model handoff, evaluation, and productization.
• Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility.
• Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs).

Technologies

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

Team Overview

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing Capital One’s AI vision to life. The team works with partners across the company to advance the state of the art in science and AI engineering, and to build and deploy proprietary solutions central to the business and delivering value to millions of customers. AI models and platforms empower teams across Capital One to enhance products using responsible and scalable approaches with high leverage impact.

Incentive Compensation

This role is eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.

Benefits

• Comprehensive, competitive, and inclusive set of health, financial and other benefits that support total well-being.

Application Window

This role is expected to accept applications for a minimum of 5 business days.

Sponsorship

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

Equal Opportunity and Workplace Statements

• 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 will consider for employment qualified applicants with a criminal history in a manner consistent with applicable laws regarding criminal background inquiries.
• 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.
• Capital One Financial is made up of several different entities. Any position posted in Canada is for Capital One Canada, in the United Kingdom is for Capital One Europe, and in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Accommodation and Recruiting Contact

• For employment accommodation requests: 1-800-304-9102 or [email protected].
• For technical support or recruiting process questions: [email protected].