Engineering Manager, Serverless Compute Platform

Databricks•Bellevue, WA

2d•$180,500 - $225,600

About The Position

The Serverless Compute Platform is the backbone of Databricks' fastest-growing products, powering massive growth in existing product lines and new emerging products. This platform manages highly scalable, efficient, and intelligent services across millions of virtual machines daily on AWS, Azure, and GCP. As Engineering Manager for the Execution Sandbox team, you will own the end-to-end delivery of this new service and the engineers building it. 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.

Requirements

5+ 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).
Bias toward operational rigor. Deep commitment to observability, SLOs, pre-mortems, and healthy on-call cultures.

Responsibilities

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.
Manage and elevate a team of strong L3-L5 engineers, establishing clear ownership boundaries and architectural doctrine. You will also hire 2-3 additional engineers to support this expanded scope.