Frontier AI Safety Red Team Specialist

Mercor; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Mercor in London seeks experienced AI Safety Red Teamers to identify vulnerabilities in frontier AI systems through adversarial testing. You will design challenging prompts, uncover model weaknesses, and evaluate AI behavior across complex, high-risk, and ambiguous topics.

Join a team focused on safety, robustness, and responsible AI, collaborating with researchers to strengthen model alignment and governance while reporting findings and contributing to benchmarks.

Qualifications

• Bachelor's degree or higher in Computer Science, Cybersecurity, Journalism, Communications, Psychology, Biology, Chemistry, Public Policy, or related discipline.
• 5+ years of professional experience in AI Safety, AI Red Teaming, Trust & Safety, cybersecurity, investigative journalism, life sciences, or related field.
• Strong analytical reasoning, prompt design, and written communication skills.
• Experience designing adversarial prompts or evaluating frontier AI systems.

Responsibilities

• Design adversarial prompts to stress-test frontier AI models.
• Identify jailbreaks, unsafe behaviours, hallucinations, and policy failures.
• Evaluate model robustness across misinformation, cyber, biosecurity, fraud, political content, and other sensitive domains.
• Document vulnerabilities and contribute to safety benchmarking and red-teaming reports.
• Collaborate with AI researchers to improve model alignment, robustness, and safety.

Skills

Adversarial testing

Prompt design

AI safety

Analytical reasoning

Written communication

Education

Bachelor’s degree or higher in Computer Science or related field

Job description

Mercor in London seeks experienced AI Safety Red Teamers to identify vulnerabilities in frontier AI systems through adversarial testing. You will design challenging prompts, uncover model weaknesses, and evaluate AI behavior across complex, high-risk, and ambiguous topics.

Join a team focused on safety, robustness, and responsible AI, collaborating with researchers to strengthen model alignment and governance while reporting findings and contributing to benchmarks.