AI Platform Engineer

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.

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

Some of the things that we look for:

• 5+ years of software engineering experience, with at least 2 years building platform, infrastructure, or developer tooling
• Proficiency in both Python and JVM languages (Java or Kotlin)
• Experience designing APIs and SDKs consumed by other engineering teams
• Strong distributed systems fundamentals: RPC, serialization, error handling, observability
• Experience with containerization, CI/CD pipelines, and cloud infrastructure (AWS preferred)
• Track record of building tools that measurably improve other engineers' velocity

Preferred Qualifications

• Experience with LLM integration patterns: model APIs, token management, streaming, tool use
• Experience with cross-language interop (gRPC, FFI, language bridges)
• Open-source contributions to developer tooling or infrastructure projects
• Familiarity with A/B testing frameworks and experiment infrastructure
• Experience supporting both research and production workloads on the same platform
• Java agent framework experience (LangChain4j)
• Ability to Travel: This role will require 25% in-person travel for purposes including but not limited to new hire onboarding, team and department offsites, customer engagements, and other company events. Actual travel expectations may vary by role and business needs.