Cybersecurity SWE — AI Safety.

Cybersecurity SWE — AI Safety is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards. Reviewers reproduce failures, write the unit test the model should have written, and explain the fix so the modeling team can target the gap.

Engineering model quality lives or dies on whether the generated code actually compiles, passes tests, and handles edge cases. AuraOne pairs experienced engineers with the modeling team to grade outputs the way a code reviewer would.

Technical roles for code review, systems evaluation, debugging, infrastructure judgment, and developer task execution.

• ↳Run and reproduce candidate code outputs in a sandboxed environment for Cybersecurity SWE — AI Safety assignments.
• ↳Grade cybersecurity swe ai safety engineering review solutions for correctness, complexity, idiomatic style, and edge-case handling.
• ↳Write minimal failing tests that demonstrate the bug a model output missed.
• ↳Compare paired solutions and rank them with a written rationale tied to the rubric.
• ↳Tag failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.
• ↳Document recurring code-generation failures so the modeling team can target them.
• ↳Calibrate against gold-standard reviews to keep inter-rater agreement above target.

• ↳Strong day-job engineering experience — you can read, run, and debug unfamiliar code for Cybersecurity SWE — AI Safety work.
• ↳Comfort writing concise unit tests that capture a single failure mode.
• ↳Familiarity with at least one of: pytest, Jest, JUnit, Go test, RSpec, or equivalent.
• ↳Clear written reasoning — your review note has to convince another senior engineer.
• ↳Reliable async availability for at least 10 hours per week.
• ↳Prior code-review or technical-interview-grading experience is a plus.

$60–$90 / hr

Expected schedule: contractor, remote specialist work with program-defined task volume and review pacing.

• Code review
• Debugging
• Unit testing
• Software engineering judgment
• Cybersecurity SWE AI Safety engineering review

AuraOne uses a shared specialist intake to confirm track fit, review readiness, and the best queue for your profile. Applications submitted from partner job boards carry the source, role, and category on the apply URL.