Part-Time DevOps & Backend Engineer

## About the role We're bringing on a part-time contractor to support our active client projects during a period of increased load. You'll work directly with our co-founder and lead engineer, who will direct your tasks and review your work. Your focus is infrastructure management, backend engineering, and the code fixes that keep our systems running and on schedule. This is hands-on work inside an existing codebase. You'll need to ramp quickly, work independently, and be responsive. Think of this as an on-call role, not a learning or hand-holding opportunity. You'll communicate with the team daily. ## Who you are - 3–5 years of professional backend / DevOps experience, you've shipped real systems and worked on your own for a while. - A serious engineer, not a vibe coder. You can explain every line of code you write or touch, and fix it by hand when needed. - Obsessed with organization, you back up and manage your work properly in GitHub. - Strong critical thinker, you can independently question problems and develop solutions. - Comfortable in modern AI-assisted IDEs (VS Code, Cursor, Windsurf, Claude Code) and able to stand behind the code they produce. - You know and have built with AI systems, frontier-model APIs and open-source models but your bread and butter is solid backend engineering. ## What you'll do - Manage and maintain infrastructure (DevOps) for our AI systems. - Test, debug, and improve an existing RAG (retrieval-augmented generation) system. - Maintain and validate our Postgres and vector databases. - Support testing of our AI agents and an API integration between an external workflow system and our custom AI system. - Write and run tests for AI/agent behavior, including non-deterministic outputs. - Document fixes and findings so the team stays in sync. ## Must-have skills - Strong Python, comfortable navigating and debugging an unfamiliar codebase fast. - DevOps / infrastructure management and backend engineering. - Postgres and vector databases. - REST API / webhook integration and debugging. - Database / data modeling fundamentals. - Experience testing and evaluating LLM-based systems (not just standard unit tests). - 3–5 years professional experience; U.S.-based and English-speaking. ## Nice to have - Hands-on with RAG systems: embeddings, chunking, retrieval evaluation. - Pydantic / Pydantic AI. - Experience building with open-source LLMs. - Experience in a consulting / client-delivery environment. - FastAPI - Experience with Hosting providers such as AWS / Digital Ocean ## What success looks