Data Security & DLP Analyst
About this role
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
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