Incident Response Engineer - AI Trainer

Evaluate AI-generated cybersecurity content - including threat analysis, vulnerability assessments, and offensive security techniques - for real-world accuracy and validity. Design and solve security-focused technical problems used to train AI systems. Write clear technical explanations and security-relevant code. Provide feedback that directly shapes the next generation of AI security models.

2+ years of hands-on experience in a cybersecurity role - such as penetration testing, red teaming, incident response, detection engineering, DFIR, malware analysis, threat intelligence, or adjacent fields, including government or military cyber operations. Some coding experience required; comfort navigating and patching a codebase is key. Fluency in English (native or bilingual level) with strong writing skills. A bachelor's degree is preferred. Cybersecurity certifications are a plus (e.g., OSCP, CRTO, GREM, GCFA, CEH, and similar). Note: Payment is made via PayPal. We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand.

Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour. Impact: help shape the future of AI technologies built for cybersecurity., Pay: $40.00 - $60.00 per hour

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for an experienced Incident Response Engineer - AI Trainer to help advance AI development. Cybersecurity platforms are increasingly powered by AI - but these systems still need practitioners with real-world experience to validate whether the outputs actually hold up in practice. That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated security content, solving technical security problems, and providing feedback that directly shapes how these systems reason about real-world threats and defenses. Some team members fit this work alongside a full-time role, while others treat it as their primary focus.