Senior Lead AI Engineer,(mlx, Agentic Ai, Gen AI Platform Services)

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 like 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, and latency.

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
  • VectorDBs
  • Guardrails
  • Memory
  • training optimization
  • inference optimization
  • hardware utilization
  • latency
  • throughput
  • cost optimization
  • AI research
  • AI systems
  • communication
  • presentation

What the JD emphasized

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

Other signals

  • foundation model training
  • large language model inference
  • similarity search
  • guardrails
  • model evaluation
  • experimentation
  • governance
  • observability