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AuraOne seeks a Safety Evaluation Red Team Specialist to stress-test AI systems with adversarial prompts and document failures with precise reproduction steps. You will work remotely, focusing on jailbreaks, policy bypasses, and prompt injection, helping patch gaps before customers see them.
Responsibilities include designing attack scenarios, scoring defenses, triaging new vectors, and maintaining a library of red-team rubrics while communicating findings clearly across teams.
Safety Evaluation Red Team Specialist is a remote red-team track for stress-testing AI systems against adversarial prompts. Reviewers craft attack scenarios, document the failure mode, and pair each successful jailbreak with the rubric clause it violated so the safety team can patch the gap.
Category: AI Safety & Red Teaming · Pay: $65–$70 / hr · Location: Remote — US-eligible · Contractor
Safety Evaluation Red Team Specialist is a remote red-team track for stress-testing AI systems against adversarial prompts. Reviewers craft attack scenarios, document the failure mode, and pair each successful jailbreak with the rubric clause it violated so the safety team can patch the gap.
Safety Evaluation Red Team Specialist is a remote red-team track for stress-testing AI systems against adversarial prompts. Reviewers craft attack scenarios, document the failure mode, and pair each successful jailbreak with the rubric clause it violated so the safety team can patch the gap.
Adversarial evaluation is how AuraOne hardens AI models before they ship to customers. Reviewers think like attackers and write up failures with enough rigor that the modeling team can reproduce, fix, and regress-test them.
Push on refusal boundaries and dual-use risk before a model ships.
Track Adversarial evaluation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US
Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.
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