An application made for this job — a tailored resume and cover letter that speak straight to the posting.
Obsidian is seeking engineers to build and operate LLM agents in production. You will ship agents used by real users, and be on the hook when they break, with visibility into impact and cost.
We value experience in production-grade agent systems, long-running jobs, and measuring improvement, adoption, and tradeoffs in real deployments. Apply with stories about your war-time fixes and lessons learned.
We are looking for engineers who build and operate LLM agents in production, and who have real visibility into how agents are actually used inside a company.
You have probably:
We are especially interested in the layers most people do not talk about: internal monoagents wired into company data, shared company memory, reusable skills and playbooks, the tool and MCP surfaces agents call, and how anyone sees what agents did and what they cost.
Applying starts with a short conversational AI interview. No coding, no take-home. We want to hear how you actually think about agent reliability, evaluation, and adoption, and the tradeoffs you have made in real systems. Bring war stories. The messier and more specific, the better.
If that screen stands out, we will invite you to a live 30 minute conversation with our team. We pay $100 to $500 for that conversation, paid on completion of the call, with the amount depending on depth of experience.