Red Team Lead — Offensive Cybersecurity AI Review.

Red Team Lead — Offensive Cybersecurity AI Review.

Red Team Lead — Offensive Cybersecurity AI Review is a remote red-team track for stress-testing AI systems against adversarial prompts.

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REL 24.09 signed REGRESSION caught

• cached OVERRIDE 19 of 142 INCIDENT gate
• halted TRACK
  
  

Adversarial evaluation

Aligned to the AuraOne specialist routing.

TYPE

Contractor

Remote-first specialist work, paid per accepted task.

LOCATION

Remote

• Independent specialist contractor
  
  

Remote — US-eligible

About The Role

Red Team Lead — Offensive Cybersecurity AI Review 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.

Stress-test model behavior, refusal boundaries, dual-use risk, and safety policy adherence before deployment.

Responsibilities

• ↳Design adversarial prompts that probe known weakness classes (jailbreak, policy bypass, prompt injection) for Red Team Lead — Offensive Cybersecurity AI Review 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.
  
  

Requirements

• ↳Demonstrated experience red-teaming AI systems, security research, or adversarial ML work for Red Team Lead — Offensive Cybersecurity AI Review 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.
  
  

Compensation

Hourly rate confirmed after the interview process.

Expected schedule: contractor, remote specialist work with program-defined task volume and review pacing.

Skills Used In Matching

• Adversarial prompting
• Red-team analysis
• Policy taxonomy
• Failure documentation
• Adversarial prompt testing
  
  

How To Apply

AuraOne uses a shared specialist intake to confirm track fit, review readiness, and the best queue for your profile. Applications submitted from partner job boards carry the source, role, and category on the apply URL.

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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.