Capital One
AI Engineer 4 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)
$197K–$246K
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 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 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 operate foundational AI systems and platform services, including agentic workflows, guardrails, evaluation, and optimized large-scale model infrastructure.
What you'll do
- Design, develop, test, deploy, and support AI components such as model inference, agents, similarity search, guardrails, evaluation, governance, and observability.
- Optimize foundation-model training and inference for scalability, cost, latency, throughput, and hardware utilization.
- Own architecture and reliability practices for AI systems, and coordinate deployment reviews across engineering, research, and product teams.
What they ask for
- Bachelor's degree in a listed or related field plus at least 4 years developing AI/ML algorithms or technologies, or a Master's degree in a listed or 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 with cost, latency, throughput, and accuracy tradeoffs.
- Experience building agentic AI systems and workflows; deploying scalable AI on cloud platforms is also preferred.
Pay
$197,300 - $225,100 USD base salary (Cambridge, MA; McLean, VA); $215,200 - $245,600 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 agentic AI and multi-agent workflows, guardrails, model evaluation, foundation-model optimization, and scalable, responsible AI infrastructure.
Model-written summary · the original posting is authoritative