Backend Infrastructure Engineer for Large-Scale AI Tracing Data

Stop reading here if you don't want to relocate to San Francisco immediately.

You can stop reading here if you want work life balance rather than just building.

Great, now we can start.

Most LLM apps break in production - you know this.

This role is about building the infrastructure that makes them reliable.

Astounding founding team, real ownership and solving hard distributed systems problems - the three hit combination.

You’ll be joining the team behind one of the the largest open-source LLM engineering platform.

Working directly with a small team, you'll be expected to relocated to San Francisco to own and scale the backend infrastructure powering terabytes of AI tracing data per day.

You'll build and optimise ingestion pipelines and make large-scale observability fast and affordable.

Your work will be open source, ship fast, and be used immediately by engineers running real AI systems in production.

Basic stack: Typescript, React, Next.JS, Supabase, tRPC

Nice to haves: LangChain, RAG, Fine Tuning, AWS, shadcn etc

This is for engineers who are high agency, strong backend fundamentals and a high ownership mindset.

This is not for engineers who want work life balance, value structure over results don't want to build in person.

Positions: Multiple across backend, product and SDK engineering.

Salary up to $200k.

No CV required to start the conversation, please apply.

To fast track your application, please message our founder Kieran on LinkedIn.