Remote Data Security & DLP Analyst for AI Training

Alignerr Corp.; États-Unis; À distance; AUD 83 000 - 152 000; Temps partiel

Avantages offerts par ce poste

Fully remote

Flexible schedule

Freelance perks

Résumé du poste

Alignerr Corp. is seeking a Data Security & DLP Analyst (AI Training) to help govern how AI systems reason about sensitive information.

Join a remote hourly-contract role and apply hands-on data loss prevention, classification, and risk assessment to real-world datasets. You’ll work with cloud, SaaS, and enterprise contexts, evaluate prevention and detection strategies, and contribute to training data used to benchmark AI safety.

Qualifications

• 2+ years of experience in data security, compliance, information risk, or security operations.
• Hands-on familiarity with DLP tools, data classification frameworks, and privacy/regulatory concepts (e.g., GDPR, HIPAA, CCPA).
• Practical understanding of how data risk plays out across modern IT environments.
• Strong analytical and written communication skills.
• Able to work independently and deliver structured, high-quality outputs.

Responsabilités

• Analyze realistic data security and DLP scenarios spanning cloud, SaaS, and enterprise environments.
• Classify data sensitivity levels, exposure paths, and policy violations based on real-world context.
• 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.
• Apply your practical knowledge to help AI reason about how sensitive information is exposed and protected.

Connaissances

Data security

DLP tools

Data classification

Privacy concepts

Analytical skills

Written communication

Independent work

Outils

Cloud security platforms

SaaS security tooling

Description du poste

Alignerr Corp. is seeking a Data Security & DLP Analyst (AI Training) to help govern how AI systems reason about sensitive information.

Join a remote hourly-contract role and apply hands-on data loss prevention, classification, and risk assessment to real-world datasets. You’ll work with cloud, SaaS, and enterprise contexts, evaluate prevention and detection strategies, and contribute to training data used to benchmark AI safety.