AI Safety Specialist - Fully Remote

Mercor; København; Remote; DKK 578,000 - 963,000; Full time

Job summary

Mercor is seeking a remote-friendly red team data specialist to test conversational AI models, identify vulnerabilities, and generate actionable data. You will document findings, follow structured playbooks, and work across projects with diverse clients.

Fluent in English and Danish, you will convey risks clearly to both technical and non-technical stakeholders. The role emphasizes adversarial thinking, rigorous methodology, and adaptability to shifting customer needs while maintaining

Qualifications

• 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.

Responsibilities

• Red team conversational AI models and agents: jailbreaks, prompt injections, misuse cases, bias exploitation, multi-turn manipulation
• 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

Skills

Red team experience

Adversarial mindset

Structured approach

Effective communicator

Adaptable

Tools

Frameworks & benchmarks

Job description

Location

Remote

Fluent Language Skills Required

English & Danish. Native fluency in English and Danish is required for this position.

Why This Role Exists

At Mercor, we believe the safest AI is the one that is already been attacked - by us. We are assembling a red team for this project - human data experts who probe AI models with adversarial inputs, surface vulnerabilities, and generate the red team data that makes AI safer for our customers.

This project involves reviewing AI outputs that touch on sensitive topics such as bias, misinformation, or harmful behaviors. All work is text-based, and participation in higher-sensitivity projects is optional and supported by clear guidelines and wellness resources. Before being exposed to any content, the topics will be clearly communicated.

What You’ll Do

• Red team conversational AI models and agents: jailbreaks, prompt injections, misuse cases, bias exploitation, multi-turn manipulation
• 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

Who You Are

• 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, conversational AI testing
• Creative probing: psychology, acting, writing for unconventional adversarial thinking

What Success Looks Like

• You uncover vulnerabilities automated tests miss
• You deliver reproducible artifacts that strengthen customer AI systems
• Evaluation coverage expands: more scenarios tested, fewer surprises in production
• Mercor customers trust the safety of their AI because you've already probed it like an adversary

Why Join Mercor

• Build experience in human data-driven AI red teaming at the frontier of safety
• Play a direct role in making AI systems more robust, safe, and trustworthy