Drimva

Capital One

AI Engineer 5 (Gen AI Platform Services: Agentic Systems)

$230K–$286K

New York, NY +4 · Full-time · Posted Oct 7, 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 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
Will consider sponsoring a new qualified applicant for employment authorization.

About the job

Build and optimize scalable AI platform services, including foundation models, inference, agentic workflows, and multi-model orchestration for banking products.

What you'll do

  • Design, develop, deploy, and support AI components and multi-model orchestration pipelines.
  • Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization.
  • Lead design and governance reviews, contribute to technical roadmaps, and mentor AI engineers.

What they ask for

  • Bachelor’s degree in a related field plus at least 6 years developing AI/ML algorithms or technologies, or a master’s degree in a related field plus at least 4 years.
  • At least 6 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.
  • Experience building agentic AI systems and workflows.

Pay

$229,900 - $262,400 USD base salary (Cambridge, MA; McLean, VA); $250,800 - $286,200 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 foundation model and LLM inference systems, agents and multi-agent workflows, similarity search, guardrails, evaluation, governance, and observability; optimize training and inference for production.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)