About this role
Data Security & DLP Analyst (AI Training) About The Role We're looking for experienced data security professionals to help train and evaluate frontier AI systems. Your real-world knowledge of how data leaks happen — and how they're stopped — will directly shape how AI reasons about sensitive information risk. This is a unique opportunity to apply your security expertise beyond traditional roles, contributing to AI that needs to understand DLP controls, exposure paths, and data protection strategies the way a seasoned practitioner does. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Analyze realistic data security and DLP scenarios across cloud, SaaS, and enterprise environments Classify data sensitivity levels, exposure paths, and policy violations Evaluate prevention, detection, and incident response strategies for accuracy and completeness Generate, label, and validate data security cases used to train and benchmark AI systems Provide expert judgment on how sensitive information risk plays out in real-world contexts Who You Are 2+ years of experience in data security, compliance, or security operations Hands-on familiarity with DLP tools, data classification frameworks, and privacy or regulatory concepts (e.g., GDPR, HIPAA, CCPA) Practical understanding of how data risk surfaces in modern enterprise and cloud environments Able to think through edge cases, ambiguous scenarios, and realistic threat patterns Strong written communication — you can clearly explain your reasoning Nice to Have Experience with cloud security (AWS, Azure, GCP) or SaaS data governance Background in security operations, incident response, or compliance auditing Familiarity with AI or data labeling workflows Why Join Us Work directly on cutting-edge AI projects with leading research labs Fully remote and flexible — work on your own schedule Freelance perks: autonomy, variety, and global collaboration Apply deep security expertise to a genuinely novel and high-impact problem Potential for ongoing work and contract extension