Capital One
AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)
$230K–$286K
New York, NY +4 · Full-time · Posted Oct 6, 2026
- Location
- New York, NY
San Francisco, CA
McLean, VA
Cambridge, MA
San Jose, CA - 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 platform services, including agentic workflows, model orchestration, guardrails, evaluation, and scalable production infrastructure.
What you'll do
- Design, build, deploy, and support AI components and multi-model orchestration pipelines.
- Optimize production AI systems for scalability, cost, latency, throughput, hardware utilization, and performance.
- Lead technical reviews and governance, contribute to platform roadmaps, and mentor AI engineers.
What they ask for
- Bachelor’s degree in a listed or related field plus 6+ years developing AI/ML algorithms or technologies, or a Master’s degree in a listed or related field plus 4+ years of such experience.
- At least 6 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading AI systems with cost, latency, throughput, and accuracy tradeoffs.
- Experience deploying scalable, responsible AI solutions on cloud platforms; the posting specifies 7+ years.
Pay
$229,900 - $262,400 USD base salary (Cambridge, MA); $229,900 - $262,400 USD base salary (McLean, VA); $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
Build agentic AI and multi-agent workflows, foundation model training and LLM inference, similarity search, guardrails, evaluation, orchestration, and optimization of production AI systems.
Model-written summary · the original posting is authoritative