AI Engineer — GTM Analytics

Join Databricks as an AI Engineer to build AI-powered analytics solutions for our go-to-market organization, leveraging cutting-edge technology and tools. At Databricks, we are passionate about enabling GTM Analytics Engineering builds the internal data and AI platform that Databricks' own go-to-market organization runs on — used by 6,000+ field users across sales, strategy, and operations. We own the number one Databricks App, the Genie agents, which are powered through the lakehouse (Unity Catalog bronze/silver/gold) beneath them. We are "Customer Zero" for Databricks: we adopt the newest Databricks and AI tooling first, in production, and pave the path for the rest of the company. We're in the middle of a step-change — moving the app from AI/BI and Genie experience to an AI-native, genie-centric platform that delivers prescriptive recommendations (not just descriptive reports), built to scale for the next 3–5 years. We build with AI in the loop end to end, and a large and growing share of our code is AI-generated and human-reviewed.

• •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).

• •Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.
• •Zone 1 Pay Range $146,600 — $201,650 USD
• •Zone 2 Pay Range $132,000 — $181,500 USD
• •Zone 3 Pay Range $124,600 — $171,400 USD
• •Zone 4 Pay Range $117,300 — $161,250 USD
• •The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

• •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.

• •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.