Data Security & DLP Analyst

Data Security & DLP Analyst (AI Training) About The Role What if your data security knowledge could help build smarter, safer AI? At Alignerr, we partner with the world's leading AI research labs to develop frontier AI models — and we need experienced data security professionals to make it happen. As a Data Security & DLP Analyst, you'll apply your real-world expertise in data loss prevention, classification, and incident response to shape how AI systems reason about sensitive information. Your hands-on experience with how data leaks actually happen is exactly what we need. • Organization: Alignerr • Type: Hourly Contract • Location: Remote • Commitment: 10–40 hours/week What You'll Do • Analyze realistic data security and DLP scenarios spanning cloud, SaaS, and enterprise environments • Classify data sensitivity levels, exposure pathways, and policy violations • Review and evaluate prevention, detection, and incident response strategies • Generate, label, and validate realistic data security cases used to train and evaluate AI models • Apply your practical knowledge of how data risk unfolds in real organizational environments Who You Are • 2+ years of experience in data security, compliance, or security operations • Familiar with DLP tools, data classification frameworks, and privacy or regulatory concepts (GDPR, HIPAA, PCI-DSS, etc.) • Practical understanding of how data risk and exposure play out in real-world environments • Able to think critically and communicate findings in a clear, structured way • Self-motivated and comfortable working independently on task-based assignments Nice to Have • Experience with cloud security platforms (AWS, Azure, GCP) or SaaS security tooling • Background in security operations, insider threat analysis, or data governance • Familiarity with AI evaluation or data labeling workflows Why Join Us • Work directly on cutting-edge AI projects with top-tier research labs • Fully remote and flexible — work on your own schedule • Freelance perks: autonomy, variety, and global collaboration • Make a meaningful impact on how AI understands and handles sensitive data • Potential for ongoing work and contract extension