Trust and Safety Policy Document QA Specialist

Trust and Safety Policy Document QA 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. Why this role matters 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. Responsibilities Design adversarial prompts that probe known weakness classes (jailbreak, policy bypass, prompt injection) for Trust and Safety Policy Document QA Specialist 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. Calibrate against the broader red-team cohort to keep coverage and severity consistent. Qualifications Demonstrated experience red-teaming AI systems, security research, or adversarial ML work for Trust and Safety Policy Document QA Specialist work. Strong written communication — your reports become the patch ticket. Comfort working in policy-grey areas with clear documentation of what was attempted and why. Familiarity with prompt-injection, jailbreak, and policy-bypass taxonomies. Reliable async availability for at least 10 hours per week. Example tasks Construct a 5-turn adversarial conversation that bypasses a specific policy clause and write up the patch ticket. Score a model's defenses against a known jailbreak pattern across 20 variants. Propose a new red-team rubric category after spotting an emerging attack vector. Reproduce a failure another reviewer reported and confirm the severity tag. Nice to have Background in offensive security, AppSec, or trust & safety operations. Experience publishing or reproducing public adversarial-ML research.Multilingual fluency for cross-language attack testing. Skills Adversarial prompting Red-team analysis Policy taxonomy Failure documentation Document annotation Legal reasoning Policy review Risk analysis Trust Safety Policy Work model Remote - US-eligible. Remote · Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US. Compensation Hourly rate confirmed after the interview process. Demonstrated experience red-teaming AI systems, security research, or adversarial ML work for Trust and Safety Policy Document QA Specialist work. Strong written communication — your reports become the patch ticket. Comfort working in policy-grey areas with clear documentation of what was attempted and why. Familiarity with prompt-injection, jailbreak, and policy-bypass taxonomies. Reliable async availability for at least 10 hours per week. #J-18808-Ljbffr