Auditors grade end-to-end AI-assisted coding sessions, judging whether each step was correct and whether the workflow was sound. It suits experienced developers who have used tools such as Cursor, Copilot or Claude Code and can write rubric-based feedback.
About the role
Evaluate the quality and correctness of AI-assisted software-development traces used to train and evaluate a frontier AI lab's models. You'll assess end-to-end coding sessions produced with AI-assisted developer tools — judging correctness, workflow soundness, and reasoning — and provide clear, rubric-based written feedback.
Basic Qualifications
- 3+ years professional software development
- Hands-on experience with AI-assisted coding tools and agentic / spec-driven workflows (Cursor, GitHub Copilot, Claude Code, or similar)
- Strong code-reading and debugging skills across full-stack or backend systems
- Ability to evaluate multi-step coding trajectories for correctness and best practice
Preferred Qualifications
- Experience with Kiro or Amazon CodeCatalyst
- Prior work evaluating or grading AI-generated code
- Contributions to developer tooling
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