Agent Engineer

Role Overview

Build and operate production LLM agents, with firsthand insight into how people across a company adopt and rely on them. This work focuses on practical agent reliability, evaluation, adoption, and the tradeoffs involved in real systems.

Qualifications

• Have shipped an agent that real users relied on and taken responsibility when it failed.
• Can assess whether an agent improved or regressed after a change.
• Have operated agents beyond a single request, including scheduled jobs, long-running work, or cloud sandboxes.
• Have observed the rollout of an internal assistant and understand both adoption and lack of adoption within an organization.
• Bring experience with internal agents connected to company data, shared company memory, reusable skills and playbooks, tool and MCP integrations, and visibility into agent activity and cost.

Work Terms

• Remote, per-task engagement.
• The process begins with a short conversational AI interview. No coding exercise or take-home assignment is required.
• Selected candidates will be invited to a live 30-minute conversation to discuss their experience with agent reliability, evaluation, adoption, and real-world engineering tradeoffs.

Compensation

Compensation is $100 to $500 per task. The live conversation is paid upon completion, with the amount based on depth of experience.

Application Process

Apply and complete the conversational screening interview, sharing specific examples of production agent work, including challenges, failures, and lessons learned. Every submission is reviewed.