Sr Director, AI Engineering

Capital One Capital One · Banking · San Francisco, CA +5

Sr. Director of AI Engineering responsible for overseeing the design, development, testing, deployment, and support of AI software components, including foundation model training, LLM inference, and optimization techniques. The role involves making build-vs-buy decisions, contributing to technical vision, and attracting/retaining AI talent.

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

  • Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields
  • AI and ML algorithms or technologies
  • people leadership experience
  • managing and leading an engineering team
  • deploying scalable and responsible AI solutions on cloud platforms
  • LLM Inference
  • Similarity Search
  • VectorDBs
  • Guardrails
  • Memory
  • Python
  • C++
  • C#
  • Java
  • Golang
  • AI research
  • AI systems
  • communication skills
  • presentation skills

Nice to have

  • AWS Ultraclusters
  • Huggingface
  • Nemo Guardrails
  • PyTorch

What the JD emphasized

  • responsible and reliable AI systems
  • world-class applied science and engineering teams
  • responsible and scalable ways
  • deliver AI-powered products
  • foundation model training
  • large language model inference
  • similarity search
  • guardrails
  • model evaluation
  • experimentation
  • governance
  • observability
  • build-vs-buy decisions
  • state-of-the-art LLM optimization techniques
  • large scale production AI systems
  • technical vision
  • long term roadmap
  • foundational AI systems
  • attract and retain top talent
  • nurture personal and professional development
  • foster a culture of learning
  • staying abreast of the state-of-the-art in AI
  • Deeply Technical
  • expertise in hardware, software, and AI
  • resilient trail blazer
  • forge new paths
  • at least 10 years of experience developing AI and ML algorithms or technologies
  • at least 8 years of experience developing AI and ML algorithms or technologies
  • 5 years of people leadership experience
  • 7 years of experience managing and leading an engineering team
  • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms
  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
  • Passion for staying abreast of the latest AI research and AI systems
  • judiciously apply novel techniques in production
  • Excellent communication and presentation skills
  • articulate complex AI concepts to peers

Other signals

  • building and deploying proprietary solutions
  • advance the state of the art in science and AI engineering
  • empower teams across Capital One to enhance their products with the transformative power of AI
  • deliver AI-powered products
  • foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability
  • invent and introduce state-of-the-art LLM optimization techniques
  • technical vision and the long term roadmap of foundational AI systems