AI Engineer — Gtm Analytics

Databricks Databricks · Data AI · IL · Remote · Sales Operations

AI Engineer role focused on building the intelligence and application layers of an AI-native platform, including Genie-powered analytics agents and LLM-driven workflows. The role involves developing agentic workflows, integrating with Databricks lakehouse and Lakebase services, and utilizing AI coding tools. Emphasis on shipping features, evaluating AI outputs, and partnering with various stakeholders.

What you'd actually do

  1. 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.
  2. Develop and integrate agentic workflows — prompts, tools/MCP integrations, retrieval, and evaluation — that turn business questions into reliable, grounded answers.
  3. Write Python and SQL against our Databricks lakehouse (Unity Catalog, Delta) and Lakebase (Postgres) services that back the apps.
  4. 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.
  5. Contribute to evaluation and quality: help measure and improve the accuracy of our AI outputs (eval sets, scorecards, regression checks).

Skills

Required

  • Python
  • SQL
  • LLMs / generative AI
  • APIs
  • prompts
  • RAG
  • Knowledge graphs
  • agents
  • AI developer tools

Nice to have

  • Databricks platform
  • AI Gateways
  • Unity Catalog
  • Databricks Apps
  • Genie
  • agentic systems
  • RAG systems
  • MCP
  • tool-calling
  • eval frameworks
  • React
  • TypeScript
  • FastAPI
  • Postgres
  • CI/CD
  • dbt
  • Spark
  • medallion architectures
  • analytics/BI

What the JD emphasized

  • 7+ years of software and AI engineering related experience
  • 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.

Other signals

  • AI-native platform
  • LLM-driven workflows
  • AI-powered surfaces
  • AI coding tools