Remote AI Safety Red Teamer for Frontier Models

Mercor; San Francisco (CA); Remote; USD 170,000 - 260,000; Full time

Job summary

Mercor is seeking 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 topics.

Responsibilities include stress-testing frontier models, identifying jailbreaks and policy failures, and collaborating with researchers to improve alignment and safety.

Qualifications

• Bachelor's degree or higher in Computer Science, Cybersecurity, Journalism, Communications, Psychology, Biology, Chemistry, Public Policy, or a related discipline.
• 5+ years of professional experience in AI Safety, AI Red Teaming, Trust & Safety, cybersecurity, investigative journalism, life sciences, or a 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

Analytical reasoning

Written communication

Model safety evaluation

Education

Bachelor's degree or higher in CS/Cybersecurity/related

Job description

Mercor is seeking 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 topics.

Responsibilities include stress-testing frontier models, identifying jailbreaks and policy failures, and collaborating with researchers to improve alignment and safety.