About the company
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
Responsibilities
- Build and ship features for AI-powered surfaces: Genie analytics agents, LLM-assisted feedback and enablement workflows, and in-app intelligence inside the GTM Hub.
- Develop and integrate agentic workflows — prompts, tools/MCP integrations, retrieval, and evaluation — that turn business questions into reliable, grounded answers.
- Write Python and SQL against our Databricks lakehouse (Unity Catalog, Delta) and Lakebase (Postgres) services that back the apps.
- Use AI coding tools (Claude Code, agentic skills) as a core part of your workflow, and help build the reusable skills and harnesses that make the whole team faster.
- Contribute to evaluation and quality: help measure and improve the accuracy of our AI outputs (eval sets, scorecards, regression checks).
- Partner with data engineers, app engineers, and strategy/ops stakeholders to take work from idea → ticket → PR → production.
- Write clean, well-documented, tested code and participate in code review (human and AI-assisted).
Requirements
- Bachelor's degree in Computer Science, Data Science, or a related field — or equivalent practical experience.
- 7+ years of software and AI engineering related experience.
- Solid fundamentals in Python and SQL.
- Hands-on exposure to LLMs / generative AI — prior work building with APIs, prompts, RAG, Knowledge graphs & agents.
- Genuine fluency with AI developer tools (e.g., Claude, Cursor) and a desire to push how far AI-assisted engineering can go.
- Strong problem-solving, curiosity, and a bias to ship and iterate; comfortable with ambiguity in a fast-moving team.
- Clear written and verbal communication; works well with both engineers and non-technical stakeholders.
Conditions
- Nice to have: Experience with the Databricks platform (AI Gateways, notebooks, jobs, Unity Catalog, Databricks Apps, Genie) or another cloud data platform.
- Building or evaluating agentic, RAG systems; familiarity with MCP, tool-calling, or eval frameworks.
- Full-stack exposure (React/TypeScript front end, FastAPI/Python back end) or data engineering (dbt, Spark, medallion architectures).
- Experience with Postgres/OLTP, CI/CD (Databricks Asset Bundles, GitHub Actions), or analytics/BI.