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/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 and responsible 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 scalable AI systems and platforms, including foundation models, LLM inference, agentic workflows, and multi-model production pipelines.
What you'll do
- Design, deploy, and support AI components and products, including model training and inference, agents, similarity search, guardrails, evaluation, governance, and observability.
- Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization; lead cost-performance reviews and technical design reviews.
- Contribute to AI platform strategy and mentor engineers across teams.
What they ask for
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 6 years developing AI/ML algorithms or technologies, or a master’s degree in one of these fields plus at least 4 years of that experience.
- 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 with scalable cloud AI, AI optimization, agentic systems, and integrating heterogeneous AI systems into production pipelines.
Pay
$229,900 - $262,400 USD base salary (McLean, VA; Cambridge, MA); $250,800 - $286,200 USD base salary (New York, NY; San Francisco, CA; San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop foundation model and LLM infrastructure, agentic and multi-agent workflows, similarity search, guardrails, evaluation, governance, observability, and optimization methods for production AI systems.
Model-written summary · the original posting is authoritative