Capital One
AI Engineer 4 (Gen AI Platform Services: Agentic Systems)
$197K–$246K
San Francisco, CA +4 · Full-time · Posted Oct 28, 2026
- Location
- San Francisco, CA
McLean, VA
Cambridge, MA
San Jose, CA
New York, NY - Experience
- 4 years developing AI/ML algorithms or technologies with a bachelor's degree, or 2 years with a master's degree; at least 4 years programming. Preferred: 6+ years deploying AI solutions on cloud platforms.
- 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 for this position.
About the job
Build and optimize production AI platforms, foundation models, and agentic systems for Capital One products and services.
What you'll do
- Design, develop, deploy, and support AI components, including model inference, agents, multi-agent workflows, guardrails, evaluation, and observability.
- Optimize large-scale AI systems for scalability, cost, latency, throughput, and hardware utilization; own architecture and reliability objectives.
- Guide technical roadmaps and reviews, ensure security and governance standards, and mentor engineering colleagues.
What they ask for
- Bachelor's degree in a listed or related field plus 4 years developing AI/ML algorithms or technologies, or a master's degree in a listed or related field plus 2 years of such experience.
- At least 4 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading AI system development and making cost, latency, throughput, and accuracy tradeoffs.
- 6+ years deploying scalable, responsible AI solutions on cloud platforms.
Pay
$197,300 - $225,100 USD base salary; $215,200 - $245,600 USD base salary
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop agentic and multi-agent AI systems, foundation-model training and inference, model optimization, similarity search, guardrails, evaluation, governance, and observability.
Model-written summary · the original posting is authoritative