About the role
Responsibilities:
- Builds AI-powered business applications end-to-end, from the Python/FastAPI service layer through to React-based user interfaces, deployed on Databricks.
- Designs and builds APIs connecting AI agents, governed data and user-facing workflows, including decision capture, audit logging and file exports for downstream systems.
- Codes rule-based decision engines in Python (e. g., allocation or replenishment logic) that work alongside ML models.
- Integrates LLM agent runtimes into applications, including tool calls, streamed responses and cited outputs.
- Writes performant SQL against governed data and ensures services operate within defined access boundaries.
- Builds interactive screens, dashboards and conversational interfaces that let users review and act on AI recommendations.
- Works closely with GenAI/ML engineers, data engineers and BAs.
Requirements:
- Primary tech stack: Python, FastAPI, REST API design, SQL, Databricks Apps, Databricks SQL, Unity Catalogue, LLM agent integration, React, TypeScript, Git / CI-CD.
- Secondary tech stack: Pydantic, Async Python, Pytest, MLflow, Delta Lake, State management, Figma-to- code.