Senior Lead AI Engineer

Capital One Capital One · Banking · San Jose, CA +3

Senior Lead AI Engineer role focused on building and deploying AI-powered products and foundational AI systems at Capital One. Responsibilities include designing, developing, testing, deploying, and supporting AI software components such as foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role involves optimizing LLM performance (scalability, cost, latency, throughput) and contributing to the technical vision and roadmap of 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

  • deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
  • designing, developing, integrating, delivering, and supporting complex AI systems
  • lead and mentor an engineering team
  • influence cross-functional stakeholders
  • LLM Inference
  • Similarity Search and VectorDBs
  • Guardrails
  • Memory
  • C++
  • C#
  • Golang
  • optimizing training and inference software
  • improve hardware utilization, latency, throughput, and cost
  • staying abreast of the latest AI research and AI systems
  • judiciously apply novel techniques in production
  • communication and presentation skills
  • articulate complex AI concepts to peers

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
  • deliver value to millions of customers
  • empower teams across Capital One to enhance their products with the transformative power of AI
  • responsible and scalable ways for the highest leverage impact