Agent Engineer
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Job Description
Agent Engineer assessing production LLM reliability, evaluation, observability, and adoption. Contract research conversation for Mercor, an AI hiring platform.
Responsibilities:
- Build and operate LLM agents in production
- Assess how agents are used by real users inside a company
- Evaluate agent performance following changes
- Operate scheduled jobs, long-running agent work, and cloud sandboxes
- Analyze adoption of internal assistants
- Work with internal monoagents, company data, shared memory, reusable skills and playbooks, tool and MCP surfaces
- Improve visibility into agent actions and costs
- Participate in a conversational AI screening interview
- Participate in a live 30-minute team conversation if selected
Requirements:
- Experience building and operating LLM agents in production
- Shipped an agent relied on by real users and taken responsibility when it failed
- Ability to evaluate whether an agent improved or worsened after a change
- Experience operating agents beyond a single request, including scheduled jobs, long-running work, or cloud sandboxes
- Visibility into internal assistant adoption within an organization
- Experience with internal monoagents connected to company data, shared company memory, reusable skills and playbooks, tool and MCP surfaces, and agent observability/costs
- Ability to discuss agent reliability, evaluation, adoption, and real-system tradeoffs
- Must complete a short conversational AI interview with no coding or take-home assignment
- Must complete a live 30-minute conversation if invited
Benefits:
- $100 to $500 payment for the live 30-minute conversation, paid on completion, depending on depth of experience
- Up to $250 for each successful referral through the referral link
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