LLM Agent Engineer - Specialist

Obsidian; New York (NY); On-site; USD 130,000 - 190,000; Full time

Job summary

Obsidian is seeking engineers who build and operate LLM agents in production with real visibility into how agents are used inside a company. You likely have shipped an agent depended on by real users and know how to tell if changes improved it.

We value experience with long-running tasks, scheduled jobs, and internal monoagents integrated with company data. You will discuss agent reliability and adoption in a live interview.

Qualifications

• Shipped an agent used by real users.
• Able to measure improvement after changes to an agent.
• Experience running long-lived or scheduled agent jobs.

Responsibilities

• Build and operate LLM agents in production environments.
• Evaluate agent performance and adoption across the org.
• Share war stories and concrete tradeoffs from real systems.

Skills

LLM Agents

Production Systems

Reliability

System Deployment

Tools

Python

Job description

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:

• Shipped an agent that real users depended on, and been on the hook when it broke.
• Figured out how to tell whether an agent got better or worse after a change.
• Run agents that outlive a single request: scheduled jobs, long-running work, cloud sandboxes.
• Watched your org build an internal assistant, and seen who adopted it and who quietly did not.

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.