Agent Engineer
Posted on August 12, 2026 · Applications until December 3, 2026
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This remote role involves building, operating, and evaluating production LLM agents, focusing on reliability, internal data integration, and user adoption. The ideal candidate has hands-on experience shipping agents that real users depend on and managing long-running agent workflows.
Description in English, as published by Mercor.
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:
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Shipped an agent that real users depended on, and been on the hook when it broke.
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Figured out how to tell whether an agent got better or worse after a change.
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Run agents that outlive a single request: scheduled jobs, long-running work, cloud sandboxes.
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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.
If that sounds like you, apply and complete the screen. We review every submission.
Open worldwide
About Mercor
Mercor is a US marketplace hiring remote experts for AI and consulting projects, from law to engineering. The original posting is on their site.
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