Type: Full-time permanent contract or an Internship with a potential follow-up offer Location: San Francisco or remote with future relocation to San Francisco (sponsored) Start: ASAP About us We're building state-of-the-art context compression. Our mission is to become the "Cloudflare for LLMs" — a compression layer embedded into most LLM pipelines by default. We're a team of ex-EPFL MSc/PhDs from dlab. We started by publishing papers, then got into YC and started making money helping companies cut their LLM costs. We run the business like a research lab: form hypotheses, kill the ones that don't work, double down on the ones that do. About you: A cracked full-stack engineer who enjoys a high-paced startup environment, takes pride in what they build and owns it end to end. Solid understanding of cloud infrastructure, deployment, and production systems on AWS. Python/basic ML Ops skills. Experience in scaling AI infra products is a plus. Proactive, strong communicator with fast response time, team player Tech Requirements Strong backend engineering fundamentals Experience with concurrency and distributed systems Experience deploying and scaling production backend services on AWS Ability to work across systems (Python + light frontend) Excellent Claude Code (or similar) user Nice to have Open-source contributions Startup experience OAuth / API auth flows Stack Backend: Python, FastAPI, PostgreSQL (Supabase), Redis, AWS Frontend: Next.js, React, TypeScript Tools: GitHub, Docker, Sentry, GitHub Actions Interview process 1. Intro call (20 min) 2. Practical technical interview (60 min) 3. Cultural interview (30 min)
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