Job Description & How to Apply Below
Outlier helps innovative companies improve AI agents through human feedback. This engineering work supports large language models designed for proactive, multi-step operation. You will assess complex system behavior, identify subtle failures, and contribute technical judgment to agent training projects.
Key Responsibilities:
Create rubrics for evaluating agent performance
Debug multi-turn agent traces and interactions
Stress test agents across real-world workflows
Identify privacy leaks and authority escalation
Detect indirect prompt injection failures
Requirements:
Two or more years of relevant experience
Strong attention to detail during technical evaluation
Clear, high-density feedback on complex behaviors
Experience handling live, non-mocked system interactions
Backend, automation, or integration engineering background
Use agent evaluation, failure analysis, and technical feedback expertise to improve Open Claw systems with Outlier.
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