Data Security & DLP Analyst (AI Training)
About The Role
We partner with the world's leading AI research labs to build smarter, safer AI systems. Now we're looking for data security professionals who understand how sensitive information is really exposed, detected, and protected in modern organizations.
This is your opportunity to take your hands-on DLP and data security experience and apply it to one of the most important challenges in AI: teaching frontier models to reason accurately about sensitive information risk.
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 realistic data-security cases used to train and benchmark AI systems
Apply your practical knowledge of how data risk plays out to help AI reason more reliably about sensitive information
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.)
You understand how data leaks actually happen — not just in theory, but in real environments
Able to communicate complex security concepts clearly in writing
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 information security policy, risk assessment, or incident response
Familiarity with AI systems or data annotation workflows
Why Join Us
Work directly on cutting-edge AI projects with top 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