Capital One
Staff AI Engineer (Remote Eligible)
$245K–$335K
San Francisco, CA +5 · Staff · Full-time · Posted Sep 23, 2026
- Location
- San Francisco, CA
US Remote
McLean, VA
Cambridge, MA
San Jose, CA
New York, NY - Experience
- 8 years developing AI/ML algorithms or technologies with a bachelor’s degree, or 6 years with a master’s degree; at least 8 years programming.
- Education
- Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Build and lead scalable, responsible AI systems and infrastructure that power products and workflows for Capital One customers and associates.
What you'll do
- Design, develop, deploy, and support AI components, including foundation model training, LLM inference, agents, search, guardrails, evaluation, and observability.
- Develop optimization techniques and architecture for production AI systems, improving scalability, cost, latency, and throughput.
- Set enterprise AI technical direction and standards; mentor teams and promote responsible AI practices.
What they ask for
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus 8 years developing AI/ML algorithms or technologies; or a Master’s degree in those fields plus 6 years.
- At least 8 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience designing AI systems with cost, latency, throughput, and accuracy tradeoffs.
- Experience deploying scalable, responsible AI solutions on cloud platforms; leadership and mentorship of engineering teams.
Pay
USD $244,700 - $279,200 base salary (Remote); USD $269,100 - $307,200 base salary (Cambridge, MA); USD $269,100 - $307,200 base salary (McLean, VA); USD $293,600 - $335,100 base salary (New York, NY); USD $293,600 - $335,100 base salary (San Francisco, CA); USD $293,600 - $335,100 base salary (San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop foundation models, LLM inference, agentic workflows, similarity search, guardrails, evaluation, and optimization for scalable, responsible production AI systems.
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