Remote AI Safety & Adversarial Evaluation Specialist

AI Trainer Jobs; United States; Remote; USD 90,000 - 96,000; Part time

Job summary

AuraOne is seeking a remote Trust and Safety Policy AI Evaluator to stress-test AI systems against adversarial prompts. You will craft attack scenarios, document failures, and map each jailbreak to the violated rubric clause to help patch gaps.

You will think like attackers, write rigorous failure reports, and help harden models before release. The role emphasizes compensation as an hourly contractor and eligibility from the US.

Qualifications

• Demonstrated experience in red-teaming AI systems, security research, or adversarial ML work for Trust and Safety Policy AI Evaluator role.

Responsibilities

• Design adversarial prompts that probe known weakness classes (jailbreak, policy bypass, prompt injection) for Trust and Safety Policy AI Evaluator assignments.
• Document every successful attack with reproduction steps and the policy clause it violated.
• Score model defenses across single-turn and multi-turn conversations.
• Triage emerging attack vectors and route them to the safety team with severity ratings.
• Maintain a personal library of attack patterns and propose new red-team rubrics.

Skills

Adversarial prompting

Red-team analysis

Policy taxonomy

Failure documentation

Trust and Safety Policy AI evaluation

Legal reasoning

Policy review

Risk analysis

Trust

Safety

Policy

Job description

AuraOne is seeking a remote Trust and Safety Policy AI Evaluator to stress-test AI systems against adversarial prompts. You will craft attack scenarios, document failures, and map each jailbreak to the violated rubric clause to help patch gaps.

You will think like attackers, write rigorous failure reports, and help harden models before release. The role emphasizes compensation as an hourly contractor and eligibility from the US.