Capital One
AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)
$230K–$286K
San Jose, CA +4 · Full-time · Posted Sep 22, 2026
- Location
- San Jose, CA
San Francisco, CA
McLean, VA
Cambridge, MA
New York, NY - Experience
- At least 6 years developing AI/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
- Will consider sponsoring a new qualified applicant for employment authorization.
About the job
Build and optimize scalable AI platforms and products, including foundation-model training and inference, agentic workflows, and unified multi-model systems.
What you'll do
- Develop, deploy, and support AI components and multi-model orchestration pipelines.
- Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization.
- Guide technical direction, governance reviews, design standards, and engineering mentorship.
What they ask for
- Bachelor's degree in a related field and at least 6 years developing AI/ML algorithms or technologies, or a master's degree in a related field and at least 4 years in that work.
- At least 6 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience building agentic AI systems and workflows, and deploying scalable AI solutions on cloud platforms.
- Experience optimizing AI training and inference, integrating heterogeneous AI systems, and defining responsible AI standards.
Pay
$229,900 - $262,400 USD base salary (McLean, VA); $229,900 - $262,400 USD base salary (Cambridge, MA); $250,800 - $286,200 USD base salary (New York, NY); $250,800 - $286,200 USD base salary (San Francisco, CA); $250,800 - $286,200 USD base salary (San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Foundation-model training and LLM inference; agentic and multi-agent workflows; similarity search, guardrails, evaluation, governance, orchestration, and optimization of production AI systems.
Model-written summary · the original posting is authoritative