AI Jailbreak & Prompt-Injection Security Expert

AI Trainer Jobs

United States

Remote

USD 96,000 - 138,000

Full time

2 days ago
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Job summary

AI Trainer Jobs is seeking a remote contractor to perform AI Jailbreak & Prompt-Injection Security testing. The role focuses on adversarial prompts, documentation, and evaluation of defenses across both single-turn and multi-turn interactions.

The work is remote with US eligibility, paid hourly, and placement depends on program demand. Candidates should bring offensive security or adversarial ML experience and strong reporting skills.

Qualifications

  • Experience red-teaming AI systems, security research, or adversarial ML work.
  • Strong written communication; reports become patch tickets.
  • Familiarity with prompt-injection, jailbreak, and policy-bypass taxonomies.

Responsibilities

  • Design adversarial prompts that probe known weakness classes (jailbreak, policy bypass, prompt injection) for AI Jailbreak & Prompt-Injection Security Expert 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.

Skills

Adversarial prompting
Red-team analysis
Policy taxonomy
Failure documentation
Jailbreak evaluation
AI model evaluation

Job description

AI Jailbreak & Prompt-Injection Security Expert 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

AI Jailbreak & Prompt-Injection Security Expert is a remote red-team track for stress-testing AI systems against adversarial prompts.

About the role

AI Jailbreak & Prompt-Injection Security Expert 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
  • Design adversarial prompts that probe known weakness classes (jailbreak, policy bypass, prompt injection) for AI Jailbreak & Prompt-Injection Security Expert 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 AI Jailbreak & Prompt-Injection Security Expert 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
  • AI Jailbreak Prompt Injection Security evaluation
  • AI model evaluation
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