LLM Agent Engineer - Production - AI Trainer

Obsidian; Chicago (IL); On-site; USD 150,000 - 190,000; Full time

Job summary

Obsidian is seeking engineers to build and operate LLM agents in production. You’ll have real visibility into how agents are used inside a company, including long-running and scheduled tasks, shared data, and reusable skills and playbooks.

No-code screening focuses on how you think about reliability and adoption, with war stories that illustrate tradeoffs in real systems. If chosen, you’ll participate in a short conversational AI interview, with compensation ranging from $100 to $500 based on

Qualifications

• Experience shipping an agent in production and handling failures
• Ability to measure agent improvements after changes
• Familiarity with long-running and scheduled agent workloads
• Understanding of internal monoagents and shared memory architectures

Responsibilities

• Design, deploy, and monitor LLM agents in production environments
• Assess deployment impact, usage, and cost of agents
• Improve reliability, evaluation, and adoption of agent-based systems
• Discuss trade-offs and war stories from real systems

Skills

LLM agents

Production systems

Agent reliability

Evaluation metrics

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.