AI Safety Red Team Expert, English & Danish

Help strengthen conversational AI systems by probing them with adversarial inputs, identifying vulnerabilities, and producing practical safety data. This remote role focuses on text-based AI red teaming in both English and Danish. Key Responsibilities

• Test conversational AI models and agents for jailbreaks, prompt injections, misuse cases, bias exploitation, and multi-turn manipulation.
• Review AI outputs involving sensitive topics, including bias, misinformation, and harmful behaviors.
• Annotate failures, classify vulnerabilities, flag systemic risks, and create high-quality human data.
• Use established taxonomies, benchmarks, and playbooks to apply testing consistently.
• Create reproducible reports, datasets, and attack cases that teams can use to improve AI systems.

• Native fluency in both English and Danish is required.
• Prior red teaming experience in AI adversarial work, cybersecurity, or socio-technical probing.
• Ability to use frameworks and benchmarks to test systems methodically.
• Clear communication skills for explaining risks to technical and non-technical audiences.
• Comfort adapting across projects and customer contexts.

• Adversarial machine learning, including jailbreak datasets, prompt injection, RLHF or DPO attacks, or model extraction.
• Cybersecurity, including penetration testing, exploit development, or reverse engineering.
• Socio-technical risk testing, including harassment or misinformation probing, abuse analysis, or conversational AI testing.
• Psychology, acting, or writing skills that support unconventional adversarial thinking.

• Remote, hourly engagement.
• All work is text-based.
• Higher-sensitivity projects are optional. Topics are communicated before exposure, with clear guidelines and wellness resources available.

• $48 to $62 per hour.

• Identify vulnerabilities that automated testing may miss.
• Expand evaluation coverage across more scenarios and help reduce unexpected production behavior.
• Deliver reproducible safety artifacts that help make AI systems more robust, safe, and trustworthy.