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Data Security & DLP Analyst (AI Training) About The Role We're looking for experienced data security professionals to help build and evaluate AI systems that reason about sensitive information risk. At Alignerr, we partner with the world's leading AI research labs — and your real-world expertise in data loss prevention and security operations will directly shape how frontier AI understands, detects, and responds to data exposure scenarios. This is a rare opportunity to apply your security knowledge to one of the most consequential technology challenges of our time. 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 across complex systems Evaluate prevention, detection, and incident response strategies for accuracy and completeness Generate, label, and validate data security cases used to train and evaluate cutting-edge AI models Apply your hands-on experience to help AI reason correctly about how data leaks actually happen in the real world Who You Are 2+ years of experience in data security, compliance, security operations, or a related field Practical familiarity with DLP tools, data classification frameworks, and privacy or regulatory concepts (e.g., GDPR, HIPAA, PCI-DSS) Strong intuition for how data risk manifests in real organizational environments Ability to think critically and communicate findings clearly in structured formats Self-motivated and comfortable working independently on task-based assignments Nice to Have Experience with cloud security platforms (AWS, Azure, GCP) or SaaS security tools Background in security consulting, incident response, or compliance auditing Familiarity with AI workflows or data annotation projects Why Join Us Work directly on frontier AI systems with top-tier research labs Fully remote and flexible — work on your own schedule Freelance perks: autonomy, variety, and global collaboration Contribute to meaningful work that makes AI safer and more trustworthy Potential for ongoing work and contract extension