Capital One
AI Engineer 4 (Gen AI Platform Services)
$197K–$246K
San Francisco, CA +4 · Full-time · Posted Oct 13, 2026
- Location
- San Francisco, CA
McLean, VA
Cambridge, MA
San Jose, CA
New York, NY - Experience
- At least 4 years developing AI/ML algorithms or technologies with a Bachelor’s degree, or at least 2 years with a Master’s degree; at least 4 years programming. Preferred: 6+ years deploying AI solutions on cloud platforms.
- Education
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields; or a Master’s degree in those fields.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Build and optimize scalable, responsible AI platforms and services, including foundation models, LLM inference, agents, and supporting infrastructure.
What you'll do
- Design, develop, deploy, and support AI components and systems, including model training and inference, agent workflows, evaluation, governance, and observability.
- Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization; own architecture and reliability objectives.
- Contribute to AI platform technical direction and lead cross-functional reviews on security, governance, and compliance.
What they ask for
- Bachelor’s degree in a related field plus at least 4 years developing AI/ML algorithms or technologies, or a Master’s degree in a related field plus at least 2 years of that experience.
- At least 4 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading AI system development with tradeoffs among cost, latency, throughput, and accuracy.
- 6+ years deploying scalable and responsible AI solutions on cloud platforms.
Pay
$197,300 - $225,100 USD base salary; $197,300 - $225,100 USD base salary; $215,200 - $245,600 USD base salary; $215,200 - $245,600 USD base salary; $215,200 - $245,600 USD base salary
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop and optimize foundation models, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Model-written summary · the original posting is authoritative