IAM Analyst for AI Security & Access Risk (Remote)

Alignerr Corp.; Dallas (TX); Remote; USD 14,000 - 55,000; Full time

Benefits offered by this job

Autonomy

Variety of tasks

Global collaboration

Job summary

Alignerr Corp. is seeking an Identity & Access Management (IAM) Analyst to help train AI systems with real-world identity scenarios. The role is remote, hourly, and part‑time, with 10–40 hours per week.

You will work alongside AI research teams to analyze IAM configurations, identify weaknesses, and provide expert feedback on enterprise identity risk. You will apply knowledge of RBAC, least-privilege, and access reviews to improve training data and assess security reasoning in AI-driven

Qualifications

• 2+ years of hands-on experience with IAM, SSO, or enterprise identity platforms.
• Solid understanding of RBAC, least-privilege principles, and access review processes.
• Familiar with how identity failures occur and how attackers exploit them.
• Analytical and detail-oriented — able to spot subtle misconfigurations and policy gaps.
• Clear written communicator who can explain complex security concepts concisely.

Responsibilities

• Analyze IAM, SSO, and access control scenarios to identify weaknesses, misconfigurations, and attack paths.
• Classify permission issues, privilege escalation vectors, and identity-related failures.
• Review zero-trust models and access design decisions for correctness and risk exposure.
• Generate and validate realistic identity security data used to train and evaluate AI systems.
• Provide structured, expert feedback on how AI reasons about enterprise identity risk.

Skills

IAM

SSO

RBAC

Zero-Trust

Tools

Okta

Azure AD

AWS IAM

Job description

Alignerr Corp. is seeking an Identity & Access Management (IAM) Analyst to help train AI systems with real-world identity scenarios. The role is remote, hourly, and part‑time, with 10–40 hours per week.

You will work alongside AI research teams to analyze IAM configurations, identify weaknesses, and provide expert feedback on enterprise identity risk. You will apply knowledge of RBAC, least-privilege, and access reviews to improve training data and assess security reasoning in AI-driven