Lead AI Engineer

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

Lead AI Engineer role focused on designing, developing, testing, deploying, and supporting AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves leveraging AI technologies and optimizing LLM performance for scalability, cost, latency, and throughput within an enterprise AI context. The position emphasizes building AI-powered products and foundational AI systems for millions of customers.

What you'd actually do

  1. Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
  2. 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.
  3. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
  4. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
  5. 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
  • private cloud
  • LLM Inference
  • Similarity Search
  • VectorDBs
  • Guardrails
  • Memory
  • C++
  • C#
  • Golang
  • training optimization
  • inference optimization
  • hardware utilization
  • latency
  • throughput
  • cost optimization
  • AI research

What the JD emphasized

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

Other signals

  • building and deploying proprietary solutions
  • advance the state of the art in science and AI engineering
  • build and deploy proprietary solutions
  • AI models and platforms empower teams across Capital One
  • deliver AI-powered products
  • foundation model training
  • large language model inference
  • similarity search
  • guardrails
  • model evaluation
  • experimentation
  • governance
  • observability
  • LLM optimization techniques
  • performance — scalability, cost, latency, throughput
  • foundational AI systems