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AI Trainer Jobs is seeking a remote Supply Chain Security Abuse Scenario Red Teamer to stress-test AI systems against adversarial prompts. You will craft attack scenarios, document failure modes, and pair jailbreaks with violated rubric clauses to help patch gaps.
The role requires reviewing prompts and analyzing adversarial behavior to improve safety and reliability. As a contractor working remotely in the US, you will assess risks, score defenses, and report findings with clear, reproducible
Supply Chain Security Abuse Scenario Red Teamer 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: Cybersecurity & Adversarial Testing · Pay: $70–$100 / hr · Location: Remote — US-eligible · Contractor
Supply Chain Security Abuse Scenario Red Teamer is a remote red-team track for stress-testing AI systems against adversarial prompts.
About the role
Supply Chain Security Abuse Scenario Red Teamer 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.
Probe AI systems for prompt injection and insecure code. Find the misuse paths.
Responsibilities
Role details
Track Adversarial evaluation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US
What you should bring
Role signals
Example tasks
Useful experience
Compensation and schedule
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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