Jailbreak Exploit Abuse Scenario Red Teamer

AI Trainer Jobs

United States

Remote

USD 96,000 - 138,000

Part time

3 days ago
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Job summary

AI Trainer Jobs is seeking a remote contractor to perform adversarial red-teaming on AI systems. You will craft jailbreak prompts, document failures with exact reproduction steps, and assess defenses across single and multi-turn conversations.

Responsibilities include triaging new attack vectors, assigning severity, and contributing to patch tickets with clear, policy-grounded rationales. Remote work eligible from the US; hourly compensation is discussed after interview.

Qualifications

  • Proven experience red-teaming AI systems or adversarial ML work.
  • Ability to document failures with rigorous steps for reproduction.
  • Familiarity with jailbreak, prompt-injection and policy taxonomy.
  • Ability to work asynchronously for 10+ hours per week.
  • Strong written communication to convert findings into patch tickets.

Responsibilities

  • Design adversarial prompts that probe known weakness classes.
  • Document every successful attack with reproduction steps and policy violations.
  • Score model defenses across single-turn and multi-turn conversations.
  • Triage emerging attack vectors and route them to the safety team.

Skills

Adversarial prompting
Red-team analysis
Policy taxonomy
Failure documentation
Jailbreak exploitation
Security review
Adversarial testing
Threat modeling
Jailbreak
Exploit

Job description

Jailbreak Exploit 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

Jailbreak Exploit Abuse Scenario Red Teamer is a remote red-team track for stress-testing AI systems against adversarial prompts.

About the role

Jailbreak Exploit Abuse Scenario Red Teamer is a remote red-team track for stress-testing AI systems against adversarial prompts.
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
  • Design adversarial prompts that probe known weakness classes (jailbreak, policy bypass, prompt injection) for Jailbreak Exploit Abuse Scenario Red Teamer 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.
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
  • Demonstrated experience red-teaming AI systems, security research, or adversarial ML work for Jailbreak Exploit Abuse Scenario Red Teamer 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.
Useful experience
  • Background in offensive security, AppSec, or trust & safety operations.
  • Experience publishing or reproducing public adversarial-ML research.
  • Multilingual fluency for cross-language attack testing.
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.

Skills used in matching
  • Adversarial prompting
  • Red-team analysis
  • Policy taxonomy
  • Failure documentation
  • Jailbreak Exploit Abuse Scenario Red Teamer evaluation
  • Security review
  • Adversarial testing
  • Threat modeling
  • Jailbreak
  • Exploit
Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake
  • The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.
  • 01 Confirm profile and eligibility details.
  • 02 Attach this role deliberately.
  • 03 Receive a human review decision or follow-up.
  • Placement timing depends on program demand and reviewer confirmation.
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