SLSQ327R637
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.
The roleAs an AI Engineer you'll help build the intelligence and application layers of that platform: Genie-powered analytics agents, LLM-driven workflows (feedback analysis, "what's new" enablement, BRD-to-plan automation), and the Databricks Apps and Lakebase services that serve them. You'll work alongside senior engineers, and you'll be expected to lean on AI coding tools heavily and thoughtfully from day one. This is a high-ownership, fast-shipping team where early-career engineers get real surface area.
What you'll do- 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).
- 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.
Databricks (AI Gateway, Unity Catalog, Delta, Jobs, Databricks Apps, Lakebase, Genie) · Python · SQL · React/TypeScript · FastAPI · Claude Code & agentic skills · GitHub + DABs CI/CD. We work in sprints, review each other's PRs, and treat AI as a first-class teammate — with the human judgment to know when it's wrong.
Pay Range Transparency
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. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- Bachelor's degree in Computer Science, Data Science, or related field, or equivalent practical experience
- 7+ years of software and AI engineering related experience
- Solid fundamentals in Python
- Solid fundamentals in SQL
- Hands-on exposure to LLMs / generative AI (APIs, prompts, RAG, knowledge graphs, agents)
- Fluency with AI developer tools (e.g., Claude, Cursor) and experience using AI coding tools
- Experience writing clean, well-documented, tested code and participating in code review
- Experience working with Databricks lakehouse technologies (Unity Catalog, Delta) and Lakebase/Postgres services
- Strong problem-solving, curiosity, bias to ship, and clear written and verbal communication
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
-
Equity Value & Accessibility — Equity grants are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
-
Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
-
Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
.png){kind=logo}
