Capital One
AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)
$197K–$246K
San Jose, CA +4 · Full-time · Posted Oct 20, 2026
- Location
- San Jose, CA
San Francisco, CA
McLean, VA
Cambridge, MA
New York, NY - Experience
- At least 4 years developing AI/ML algorithms or technologies with a bachelor's degree, or at least 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 operate scalable AI systems and platform services, including foundation-model training, LLM inference, agent workflows, and production optimization.
What you'll do
- Design, develop, test, deploy, and support AI components and systems.
- Optimize foundation models and production AI systems for scalability, cost, latency, throughput, and hardware utilization.
- Guide technical architecture and roadmap, reliability objectives, and deployment reviews for foundational AI systems.
What they ask for
- Bachelor’s degree in a related field plus at least 4 years developing AI/ML algorithms or technologies, or a master’s degree in a related field plus at least 2 years of that 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 (McLean, VA); $197,300 - $225,100 USD base salary (Cambridge, MA); $215,200 - $245,600 USD base salary (New York, NY); $215,200 - $245,600 USD base salary (San Francisco, CA); $215,200 - $245,600 USD base salary (San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop and optimize foundation models and LLM inference, agentic and multi-agent workflows, similarity search, guardrails, evaluation, governance, and observability for responsible production AI.
Model-written summary · the original posting is authoritative