AI Summary
Shape AI systems' understanding of data risk by analyzing real-world security scenarios and policy violations. Classify data sensitivity, evaluate prevention strategies, and generate training cases for AI models. Requires 2+ years of hands-on data security experience with DLP tools and compliance frameworks.
Key Highlights
Develop AI reasoning for data risk in cloud, SaaS, and enterprise environments
Classify data sensitivity levels and policy violations across modern systems
Generate and validate training data for AI models on security incidents
Key Responsibilities
Analyze realistic data security and DLP scenarios spanning cloud, SaaS, and enterprise environments
Classify data sensitivity levels, exposure pathways, 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 models
Help AI systems develop a nuanced, real-world understanding of how data risk unfolds
Technical Skills Required
Benefits & Perks
Fully remote
Freelance perks: autonomy, variety, and collaboration
Meaningful work on AI safety and capability
Nice to Have
Experience with cloud security, CASB, or SaaS data governance tools
Background in security consulting, incident response, or risk advisory
Familiarity with AI evaluation or data annotation workflows
Relevant certifications (CISSP, CISM, CISA, Security+, etc.)
Job Description
Data Security & DLP Analyst (AI Training)
About The Role
We're partnering with leading AI research labs to build AI systems that genuinely understand how sensitive data is exposed, detected, and protected in the real world. To do that, we need experienced data security professionals who know how breaches and policy violations actually happen — not just in theory, but in practice.
This is a rare opportunity to apply your security expertise in a new and meaningful way: shaping the next generation of AI reasoning around data risk.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
- Analyze realistic data security and DLP scenarios spanning cloud, SaaS, and enterprise environments
- Classify data sensitivity levels, exposure pathways, 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 models
- Help AI systems develop a nuanced, real-world understanding of how data risk unfolds
Interested in remote work opportunities in Cyber Security? Discover Cyber Security Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- 2+ years of hands-on experience in data security, compliance, or security operations
- Familiar with DLP tools, data classification frameworks, and privacy or regulatory standards (e.g., GDPR, HIPAA, CCPA)
- Practical knowledge of how data risk manifests across modern enterprise environments
- Able to think through realistic attack paths, misconfigurations, and control gaps
- Strong written communication — you can explain complex security concepts clearly
- Self-directed and comfortable working asynchronously on task-based projects
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- Experience with cloud security, CASB, or SaaS data governance tools
- Background in security consulting, incident response, or risk advisory
- Familiarity with AI evaluation or data annotation workflows
- Relevant certifications (CISSP, CISM, CISA, Security+, etc.)
- Work directly on frontier AI systems at the cutting edge of AI safety and capability
- Fully remote and flexible — work on your own schedule
- Freelance perks: autonomy, variety, and collaboration with a global expert community
- Meaningful work that helps AI reason more responsibly about sensitive data
- Potential for ongoing work and contract extension
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