Senior Director, AI Engineering -agentic AI Platform(remote Eligible)

Capital One Capital One · Banking · San Francisco, CA +4 · Remote

Senior Director of AI Engineering responsible for the Agentic AI Platform. This role involves overseeing the design, development, testing, deployment, and support of AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role also focuses on making build-vs-buy decisions, inventing LLM optimization techniques, and contributing to the technical vision and roadmap of foundational AI systems. The candidate will also be responsible for attracting and retaining AI talent and fostering a culture of learning.

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. Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
  3. Make high judgment build-vs-buy decisions across 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

  • Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing or leading AI and ML algorithms or technologies
  • At least 5 years of people leadership experience

Nice to have

  • 7 years of experience managing and leading an engineering team
  • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory)
  • Master's degree in Computer Science, Computer Engineering, or relevant technical field
  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

What the JD emphasized

  • At least 5 years of people leadership experience
  • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory)

Other signals

  • AI-powered products
  • foundation model training
  • large language model inference
  • similarity search
  • guardrails
  • model evaluation
  • experimentation
  • governance
  • observability
  • LLM optimization techniques
  • foundational AI systems