Engineering Manager, Serverless Compute Platform

Databricks


Job Location:

Bellevue, WA - USA

Monthly Salary: Not Disclosed
Posted on: 3 days ago
Vacancies: 1 Vacancy

Job Summary

RDQ427R100

At Databricks we are passionate about helping data teams solve the worlds 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 worlds best AI and data infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer obsessed we leap at every opportunity to solve technical challenges from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And were only getting started.

The Serverless Compute Platform is the backbone of Databricks fastest-growing products. It is powering massive growth in our existing product lines (e.g. Generic Compute SQL) as well as new and emerging products (e.g. Lakewatch interactive compute). Behind this hockey stick growth is a set of highly scalable efficient and intelligent services managing tens of millions of virtual machines daily across 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.

The impact you will have:

  • Own a 01 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 we look for:

  • 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.
  • Build and scale a high-caliber team. 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.

Required Experience:

Manager

RDQ427R100At Databricks we are passionate about helping data teams solve the worlds 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 worlds best AI and data infrastructure platfor...

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