At Databricks, we are passionate about helping enterprises that build ML models and AI agents deliver high-quality AI to production fast. Founded by engineers, and customer obsessed, we leap at every opportunity to tackle technical challenges, from designing great developer experiences to building reliable systems at global scale. And we're only getting started.

Our team builds the MLOps and LLMOps platform that millions of AI developers and ML practitioners use to track model training experiments, manage model registry, observe and evaluate AI agents. We're the team behind MLflow, the most widely adopted open-source AI engineering platform with more than 30 million package downloads per month, and its managed service used by thousands of organizations globally. We're now expanding to Bengaluru, India, and building our first AI engineering team there from scratch to work on this platform.

As a Staff Software Engineer and a founding member of the Bengaluru team, you'll be the team's technical lead. You'll set the platform strategy and architecture, drive alignment with partner teams, and lead the team to deliver a world-class MLOps and LLMOps platform, while staying hands-on.

Check out our recent blog post: coSTAR: How we ship AI agents at Databricks fast, without breaking things

The impact you will have:

• Define the platform strategy and long-term architecture.
• Lead engineering efforts from design to production rollout, with high standards for performance, correctness, and reliability.
• Solve hard problems in ingesting and querying traces, metrics, and artifacts at scale, and in evaluating AI agents in production.
• Align product, research, and engineering teams across sites on technical direction and trade-offs.
• Shape APIs and developer experiences that make it easy for customers to ship AI.
• Mentor senior engineers through design reviews and technical discussions.
• Represent the team externally through blog posts, talks, and open-source contributions to popular AI frameworks.

What we look for:

• 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 for other teams.
• Strong foundation in algorithms, data structures, and system design.
• Strong experience with backend technical stacks such as Scala or Java.
• Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes.
• Engineering maturity in security, correctness, and operational excellence.
• Proven track record as a technical lead, driving architecture decisions and delivering complex, high-impact projects end-to-end.
• Ability to lead through influence across teams.
• Strong communication skills and a passion for mentoring engineers.
• Experience with ML or LLM systems is a plus.