Engineering Manager, Serverless Compute Platform
Core
Architect and launch a 0→1 execution sandbox service that unifies CPU and GPU cluster management for non-Spark compute workloads (Notebooks, AI Agents, Remote UDFs) on Databricks' Serverless platform.
Role type
Engineering Manager, Serverless Compute Platform
Builds
Execution Sandbox Service powering non-Spark compute workloads across AWS, Azure, and GCP
Domain
Cloud Infrastructure / Distributed Systems / Multi-cloud (AWS, Azure, GCP)
Deliverable
production ML models | product features | infrastructure
Required skills
managing engineers building distributed systems, control-plane or orchestration services, deep technical fluency in infrastructure systems, multi-cloud or multi-region service deployment, operational rigor (observability, SLOs, pre-mortems), building and scaling high-caliber teams
Preferred skills
none stated
Technologies
AWS, Azure, GCP
Responsibilities
Own end-to-end delivery of a new service from inception to production scale, unify fragmented compute surface by converging CPU and GPU cluster management paths, collaborate across 5+ partner organizations to drive alignment on API contracts and shared milestones, shape product strategy by partnering with Product Management to leverage sandbox primitives for future offerings, build and scale a team of L3-L5 engineers including hiring 2-3 additional engineers
Seniority
Manager, building and scaling teams
