Staff Software Engineer Databricks AI
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will set platform strategy and long-term architecture while remaining hands-on. You will lead engineering from design through production rollout, solve large-scale trace, metric, and artifact challenges, align partner teams on technical direction, shape APIs and developer experiences, mentor senior engineers, and contribute externally through writing, talks, and open source.
Requirements
- BS or higher in Computer Science or a related field
- 10+ years of experience developing large-scale distributed systems, scaling infrastructure, or building platforms and developer tools
- Strong foundation in algorithms, data structures, and system design
- Experience with backend stacks such as Scala or Java
- Experience with AWS, Azure, GCP, Docker, or Kubernetes
- Engineering maturity in security, correctness, and operational excellence
- Proven technical-lead experience driving architecture decisions and high-impact projects end-to-end
- Ability to lead through influence across teams
- Strong communication skills and mentoring ability
Responsibilities
- Define platform strategy and long-term architecture
- Lead engineering efforts from design through production rollout
- Solve large-scale trace, metric, artifact, and AI-agent evaluation challenges
- Align product, research, and engineering teams on technical direction and trade-offs
- Shape APIs and developer experiences
- Mentor senior engineers through design reviews and technical discussions
- Represent the team through blog posts, talks, and open-source contributions