The posting, in Starburst's own words
archived Sep 17, 2026About Starburst
Starburst delivers enterprise intelligence at scale by giving organizations secure, governed access to all their data, wherever it lives. Built for distributed data environments, Starburst helps enterprises power AI and analytics without the cost and complexity of traditional data consolidation. With open standards including Trino and Apache Iceberg, Starburst enables trusted access to complete enterprise context while helping organizations avoid vendor lock-in. Leading global enterprises trust Starburst to fuel AI, analytics, and enterprise intelligence. Learn more at starburst.ai .
About the Team
We build the AI layer for Starburst's products, including AIDA. We design agents that let users ask questions in natural language and get accurate, grounded answers backed by their actual data. We operate with startup speed inside an enterprise company, shipping weekly and measuring results. This is the first dedicated platform engineering hire on the team.
Read the full posting ↓
Role Summary
You will build the shared development primitives that make multiple product teams faster, with clean abstractions across the Python/JVM boundary. This role is a force multiplier: instead of building product features directly, you build the platform, SDK, and tooling that enables every other engineer on the team to ship faster. You will own the developer experience for agent development at Starburst, building from 0 to 1 and scaling across teams. Your work is measured by other engineers' velocity, not your own feature output.
As an AI Platform Engineer at Starburst, you will:
Design and build an agent development SDK that abstracts common patterns (tool registration, context management, evaluation hooks, prompt management) Build the language bridge between Python (AI ecosystem) and JVM (Starburst platform) with type safety, error propagation, and observability across the boundary Create developer tooling: local development environments, debugging tools, test harnesses, CI integration Define and maintain API contracts between the AI layer and the Starburst platform Build shared infrastructure: model gateway, observability pipeline, experiment framework Develop unified, product-agnostic components used across multiple products Own platform health beyond feature delivery: performance, reliability, developer ergonomics