Capital One
AI Engineer 4 (LLM Gateway, FM Hosting)
$197K–$246K
San Jose, CA +3 · Full-time · Posted Oct 9, 2026
- Location
- San Jose, CA
McLean, VA
Cambridge, MA
New York, NY - Experience
- 4+ years developing AI/ML algorithms or technologies with a bachelor’s degree, or 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 infrastructure and products, including foundation-model training and LLM inference, while optimizing production performance and reliability.
What you'll do
- Design, deploy, and support AI systems, including inference, agents, similarity search, guardrails, evaluation, and observability.
- Develop optimization techniques and improve AI-system scalability, cost, latency, throughput, and hardware utilization.
- Own architecture and reliability practices, and guide deployment reviews for security, governance, and compliance.
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 such experience.
- At least 4 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading AI system development with cost, latency, throughput, and accuracy tradeoffs.
- 6+ years deploying scalable, responsible AI solutions on cloud platforms.
Pay
$197,300 - $225,100 USD base salary (Cambridge, MA); $197,300 - $225,100 USD base salary (McLean, VA); $215,200 - $245,600 USD base salary (New York, NY); $215,200 - $245,600 USD base salary (San Jose, CA)
Tools
Python, Go, Scala, CUDA, Java, AWS Ultraclusters, Huggingface, PyTorch
AI focus
Develop foundation-model and LLM infrastructure, inference systems, agents, and AI optimization techniques for scalable production use.
Model-written summary · the original posting is authoritative