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 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 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 foundational AI platforms and production systems, including foundation models, LLM inference, agentic workflows, and multi-model orchestration for Capital One products.
What you'll do
- Design, develop, deploy, and support AI software components and production systems.
- Optimize training and inference performance, scalability, cost, latency, throughput, and hardware utilization.
- Shape technical roadmaps and standards, lead design reviews and governance, and mentor AI engineers.
What they ask for
- Bachelor’s degree in a related field plus 6 years developing AI/ML algorithms or technologies, or a master’s degree in a related field plus 4 years.
- At least 6 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience deploying scalable, responsible AI on cloud platforms; 7 years specified.
- Experience with agentic AI systems, AI optimization, and architecting heterogeneous AI systems.
Pay
$229,900 - $262,400 USD base salary; $250,800 - $286,200 USD base salary
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop foundation models, LLM inference, agentic and multi-agent workflows, similarity search, guardrails, model evaluation, governance, observability, and multi-model orchestration; optimize AI training and inference systems.
Model-written summary · the original posting is authoritative