Capital One
AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)
$230K–$286K
San Jose, CA +4 · Full-time · Posted Sep 18, 2026
- Location
- San Jose, CA
San Francisco, CA
McLean, VA
Cambridge, MA
New York, NY - Experience
- At least 6 years developing AI and ML algorithms or technologies with a bachelor’s degree, or at least 4 years with a master’s degree; at least 6 years programming. Preferred: 7 years deploying scalable 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.
About the job
Build and optimize foundational AI systems and production services, including foundation models, LLM inference, agent workflows, and orchestration pipelines for Capital One products.
What you'll do
- Design, develop, deploy, and support AI components such as model inference, agents, similarity search, guardrails, evaluation, governance, and observability.
- Optimize large-scale AI systems for scalability, cost, latency, throughput, and hardware utilization; lead cost-performance reviews.
- Contribute to technical roadmaps and design standards, and mentor AI engineers.
What they ask for
- Bachelor’s degree in a listed or related field plus at least 6 years developing AI/ML algorithms or technologies, or a Master’s degree in a listed or related field plus at least 4 years.
- At least 6 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.
- Experience deploying scalable AI on cloud platforms and building agentic workflows.
Pay
$229,900 - $262,400 USD base salary (McLean, VA and Cambridge, MA); $250,800 - $286,200 USD base salary (New York, NY, San Francisco, CA, and San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop and optimize foundation-model and LLM services, agentic and multi-agent workflows, similarity search, AI orchestration, and responsible, scalable production AI systems.
Model-written summary · the original posting is authoritative