AI Red-Teamer — Adversarial AI Testing
Posted Today by Great Value Hiring
Negotiable
Undetermined
Remote
United Kingdom
Summary: The AI Red-Teamer role focuses on adversarial AI testing, requiring candidates to red-team AI models and agents through various techniques such as jailbreaks and prompt injections. The position is remote-friendly, catering to candidates in the US, UK, and Canada, and can be either full-time or part-time. Candidates are expected to document findings and support diverse projects while communicating risks effectively to stakeholders.
Key Responsibilities:
- Red-team AI models and agents: jailbreaks, prompt injections, misuse cases, exploits
- Generate high-quality human data: annotate failures, classify vulnerabilities, and flag systemic risks
- Apply structure: follow taxonomies, benchmarks, and playbooks to keep testing consistent
- Document reproducibly: produce reports, datasets, and attack cases customers can act on
- Flex across projects: support different customers, from LLM jailbreaks to socio-technical abuse testing
Key Skills:
- Prior red-teaming experience (AI adversarial work, cybersecurity, socio-technical probing)
- Curiosity and adversarial mindset: instinctively push systems to breaking points
- Structured approach: use frameworks or benchmarks, not just random hacks
- Strong communication skills: explain risks clearly to technical and non-technical stakeholders
- Adaptability: thrive on moving across projects and customers
Salary (Rate): £111.00/hr
City: undetermined
Country: United Kingdom
Working Arrangements: remote
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
AI Red-Teamer — Adversarial AI Testing [$54-$111/hr]
Location : Remote-friendly (US time zones); Geography restricted to US, UK, Canada
Type : Full-time or Part-time
Role Responsibilities
- Red-team AI models and agents: jailbreaks, prompt injections, misuse cases, exploits
- Generate high-quality human data: annotate failures, classify vulnerabilities, and flag systemic risks
- Apply structure: follow taxonomies, benchmarks, and playbooks to keep testing consistent
- Document reproducibly: produce reports, datasets, and attack cases customers can act on
- Flex across projects: support different customers, from LLM jailbreaks to socio-technical abuse testing
Good Candidature
- You bring prior red-teaming experience (AI adversarial work, cybersecurity, socio-technical probing)
- You’re curious and adversarial: you instinctively push systems to breaking points
- You’re structured: you use frameworks or benchmarks, not just random hacks
- You’re communicative: you explain risks clearly to technical and non-technical stakeholders
- You’re adaptable: thrive on moving across projects and customers
Nice-to-Have Specialties
- Adversarial ML: jailbreak datasets, prompt injection, RLHF/DPO attacks, model extraction
- Cybersecurity: penetration testing, exploit development, reverse engineering
- Socio-technical risk: harassment/disinfo probing, abuse analysis
- Creative probing: psychology, acting, writing for unconventional adversarial thinking