Remote IAM Analyst for AI Security Training

Alignerr; France; Sur place; EUR 34 000 - 83 000; Plein temps

Avantages offerts par ce poste

Autonomy

Freelance perks: autonomy, variety, &

Résumé du poste

Alignerr is seeking an Identity & Access Management (IAM) Analyst for AI training. This remote hourly contract role asks for 2+ years in IAM/SSO with a deep understanding of RBAC and least-privilege access, plus the ability to work asynchronously on task-based assignments.

You will analyze IAM scenarios, classify privilege issues, and evaluate zero-trust designs to support AI systems training and benchmarking while providing concrete feedback to improve AI risk reasoning.

Qualifications

• 2+ years of hands-on experience with IAM, SSO, or enterprise identity platforms.
• Solid understanding of RBAC, least-privilege models, and access review processes.
• Familiar with how identity failures occur in practice and how attackers exploit them.
• Detail-oriented with strong written communication skills.
• Able to work independently and asynchronously on task-based assignments.

Responsabilités

• Analyze realistic IAM, SSO, and access control scenarios to identify weaknesses, misconfigurations, and failure points.
• Classify permission issues, privilege escalation paths, and identity-related security failures.
• Evaluate zero-trust architectures and access design decisions for accuracy and risk.
• Generate and validate realistic identity security data used to train and benchmark AI systems.
• Provide structured, expert feedback that directly shapes how AI reasons about IAM risk.

Connaissances

IAM

SSO

RBAC

Least-privilege

Access reviews

Outils

Okta

Azure AD

Ping

SailPoint

Description du poste

Alignerr is seeking an Identity & Access Management (IAM) Analyst for AI training. This remote hourly contract role asks for 2+ years in IAM/SSO with a deep understanding of RBAC and least-privilege access, plus the ability to work asynchronously on task-based assignments.

You will analyze IAM scenarios, classify privilege issues, and evaluate zero-trust designs to support AI systems training and benchmarking while providing concrete feedback to improve AI risk reasoning.