RDQ427R369

At Databricks, we are passionate about enabling data teams to 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 data and AI infrastructure platform so our customers can use deep data insights to improve their business.

Our Developer Ecosystem organisation shapes how developers and the AI agents working for them build on the Databricks Data and AI Platform, from within the product to the tools they already use.

We are hiring an Engineering Manager to lead our declarative deployment framework, which turns data and AI projects into versioned, reviewable, repeatable software. It is one product with two entry points. Third-party developers use our open-source CLI from their IDEs, terminals, and CI/CD systems. First-party, they author, deploy and inspect the same projects inside the Databricks workspace. In both, AI agents increasingly do the work: coding agents drive the CLI, and our in-product AI assistant authors and deploys projects alongside the developer. Thousands of organisations run their CI/CD on it, and it is one of the fastest-growing parts of the platform.

The team owns the deployment engine and CLI, the in-workspace authoring and deployment experience, and the metadata service and deployment history that record every deployment. The hard problems are real infrastructure-as-code problems: reconciling declared and live state, making plans safe for humans and agents to approve, keeping visual authoring and code in sync, and shipping weekly releases that remain backwards-compatible for our largest customers.

The impact you will have

Lead and grow the team: Manage a team of senior engineers across three closely connected areas (the deployment engine and open-source CLI, the in-workspace authoring and deployment experience, and deployment history and metadata), working with strong tech leads. Hire, coach and promote, and grow engineers into tech leads.
Make agentic development the default path: Shape how developers and AI agents author, validate and deploy projects, both inside the workspace and from the developer's own coding agent. Design the tools, skills and guardrails so agents get the same safety and auditability as humans.
Own the strategy and roadmap: Partner with Product and Design to set a multi-quarter roadmap for declarative deployment: agentic development, governed deployments and deployment history, enterprise CI/CD, and new resource coverage. Make the trade-offs explicit when the demand is larger than the team.
Raise the bar on execution and operational excellence: Run a predictable delivery process for a fast-moving, open-source product with frequent releases. Own reliability, on-call health, incident response and the quality bar for a tool customers depend on to ship to production.
Treat backward compatibility as a product feature: Lead engine and configuration migrations without forcing customers through a flag day, and communicate change clearly to customers, the community and field teams.
Lead across the platform: Drive alignment with the many platform teams whose resources and services the framework deploys, and with our sibling teams in Developer Ecosystem (SDKs, CLI, IaC provider, IDE). Make the whole toolchain feel like one product.

What we look for

5+ years managing software engineering teams, and 8+ years of software engineering experience overall.
A track record of building and shipping developer tools or platforms used by many external developers or internal teams, such as infrastructure-as-code, deployment or CI/CD systems, CLIs, SDKs, or internal developer platforms.
A deep understanding of declarative systems and deployment workflows: plan/apply, state management, drift and reconciliation, environment promotion, GitOps.
Enough technical depth to engage on architecture and trade-offs with senior and staff engineers, and to hold a high-quality bar for public, versioned interfaces.