Engineering Manager, Serverless Compute PlatformActive$181K

Databricks
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The opportunity

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best AI and data…

What you'll do

  • You will inherit a team of strong senior ICs who have already delivered an: initial preview. Your job is to build out the full vision, guide evolution, and scale the team.

  • You will ensure strong execution health and that the service launches with: production-grade reliability spanning a range of use cases, e.g. GPU onboarding, UDF generalization, and managed REPL.

  • Own a 0→1 service with platform-wide blast radius. Architect and launch the: Execution Sandbox Service from inception to production scale. This greenfield provisioning layer will power all non-Spark compute workloads on Serverless (Notebooks, AI Agents, Remote UDFs).

  • Unify a fragmented compute surface. Converge disparate CPU and GPU cluster: management paths into a single provisioning service, eliminating parity bugs and enabling consistent product experiences.

  • Collaborate across 5+ partner organizations. Drive alignment on API contracts: and shared milestones across Serverless Platform, AI Runtime, Lakeguard, and product teams.

  • Shape product strategy through deep technical understanding. Partner with: Product Management to leverage this new sandbox primitive for future offerings like serverless command execution APIs and FaaS-style workloads.

What they're looking for

  • + years managing engineers building and operating distributed systems in: production, ideally control-plane or orchestration services
  • BS or higher in Computer Science or a related field. Equivalent practical experience is equally valued.
  • Deep technical fluency in infrastructure systems. Ability to deeply review: architecture docs, challenge design tradeoffs (e.g., state machine design, API boundaries), and coach senior ICs.
  • Experience with multi-cloud or multi-region service deployment (AWS, Azure, GCP).