AI Engineer (GTM Analytics)

TL;DR

AI Engineer (AI Engineering): Building and optimizing an AI-native, genie-centric platform for GTM analytics with an accent on agentic workflows, LLM-driven automation, and retrieval-augmented generation. Focus on developing prescriptive recommendations, integrating tool-calling capabilities, and improving the accuracy of AI outputs through evaluation sets.

Location: Must be based in the United States

Salary: $117,300 — $201,650 USD (depending on zone)

Company

Databricks is the data and AI company providing a Data Intelligence Platform to over 10,000 organizations worldwide to unify data, analytics, and AI.

What you will do

• Build and ship features for AI-powered surfaces, including Genie analytics agents and LLM-assisted feedback workflows.
• Develop and integrate agentic workflows involving prompts, MCP integrations, retrieval, and evaluation.
• Write Python and SQL against the Databricks lakehouse (Unity Catalog, Delta) and Lakebase (Postgres) services.
• Utilize AI coding tools like Claude Code to build reusable skills and harnesses that increase team velocity.
• Measure and improve the accuracy of AI outputs using eval sets, scorecards, and regression checks.
• Collaborate with data engineers, app engineers, and stakeholders to drive features from idea to production.

Requirements

• Bachelor's degree in Computer Science, Data Science, or equivalent practical experience.
• 7+ years of software and AI engineering related experience.
• Solid fundamentals in Python and SQL.
• Hands-on experience with LLMs, generative AI, RAG, knowledge graphs, and agents.
• Genuine fluency with AI developer tools such as Claude and Cursor.
• Must be based in the United States.

Nice to have

• Experience with the Databricks platform (AI Gateways, Unity Catalog, Genie, Databricks Apps).
• Experience building or evaluating agentic/RAG systems and familiarity with MCP or tool-calling.
• Full-stack exposure (React/TypeScript frontend, FastAPI/Python backend) or data engineering (dbt, Spark).
• Experience with Postgres/OLTP and CI/CD tools like GitHub Actions or Databricks Asset Bundles.

Culture & Benefits

• High-ownership, fast-shipping environment where engineers receive significant surface area.
• Culture that treats AI as a first-class teammate and encourages AI-assisted engineering.
• Comprehensive benefits and perks tailored to the employee's specific region.
• Commitment to fair, equitable compensation and a diverse, inclusive workplace.