Engineering Director, Spatial Flex

Google Google · Big Tech · Sunnyvale, CA +2

Engineering Director for Spatial Flex team, responsible for managing Google's global compute, storage, and AI/ML resources. The role focuses on shaping infrastructure for next-generation demands, optimizing resource efficiency, and leading engineering teams to deploy complex software solutions. Requires strong technical leadership, roadmap development, and experience with cloud infrastructure and AI/ML concepts.

What you'd actually do

  1. Provide technical vision and strategy. Build a multi-year technical roadmap, balancing short- and long-term technology investments in a commercial, mission-critical environment.
  2. Partner closely and influence product management, product engineering, and other Google engineering teams to improve speed, quality, and ease.
  3. Build and lead an engineering team to innovate, invent, implement, and deploy complex software solutions.
  4. Unlock roadblocks at corporate level and cultivate collaboration with senior technologists across Google through leadership, creativity, intelligence, and presence.
  5. Develop and grow talent through effective mentoring, coaching, succession planning, and retention strategies for key talent. Attract great talent internally and externally.

Skills

Required

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 15 years of leadership experience.
  • Experience in creating roadmaps balancing engineering resources and business goals.
  • Experience as a technical leader in influencing multiple teams of engineers concurrently while partnering on development initiatives.

Nice to have

  • Experience in building and running cloud infrastructure (private or public cloud) or large-scale service systems that are highly available and reliable.
  • Familiarity with AI/ML concepts, especially in areas such as Machine Learning, Inference, Performance Optimization, Capacity Management, and Inference Efficiency and Optimizations.
  • Ability to learn AI specifics.

What the JD emphasized

  • AI/ML platforms
  • data centers
  • compute, storage, and AI/ML resources globally
  • planet-scale resources
  • workload footprint management
  • inference efficiency and optimizations

Other signals

  • AI/ML platforms
  • data centers
  • compute, storage, and AI/ML resources globally
  • planet-scale resources
  • workload footprint management
  • inference efficiency and optimizations