Senior Lead AI Engineer (ai Foundations, LLM Core and Agentic Ai)

Capital One Capital One · Banking · New York, NY +4

Senior Lead AI Engineer role focused on AI Foundations, LLM Core, and Agentic AI. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, and agentic systems. The role involves optimizing LLM performance for scalability, cost, and latency, and contributing to the technical vision and roadmap for foundational AI systems. Requires strong engineering and mathematics foundation, expertise in Python/Go/Scala/Java, and experience with cloud platforms and AI technologies like Huggingface, VectorDBs, and PyTorch.

What you'd actually do

  1. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
  2. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
  3. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
  4. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Skills

Required

  • Python
  • Go
  • Scala
  • Java
  • Computer Science
  • AI
  • Electrical Engineering
  • Computer Engineering

Nice to have

  • AWS
  • Google Cloud
  • Azure
  • Huggingface
  • VectorDBs
  • Nemo Guardrails
  • PyTorch
  • C++
  • C#
  • LLM Inference
  • Similarity Search
  • Guardrails
  • Memory
  • training optimization
  • inference optimization
  • cloud platforms

What the JD emphasized

  • responsible and reliable AI systems
  • responsible and scalable ways
  • scalable and responsible AI solutions

Other signals

  • foundation model training
  • large language model inference
  • similarity search
  • guardrails
  • model evaluation
  • agentic AI