As an Information Security Engineer – AI Identity Security, you will be responsible for securing the identities associated with AI systems, including models, agents, services, pipelines, and non-human actors that interact with data, infrastructure, and other systems. This role focuses on the discovery, lifecycle management, control enforcement, and monitoring of AI identities to ensure they are properly governed, least-privileged, and continuously assessed for risk.
Key Responsibilities
AI Identity Discovery & Inventory• Design and operate mechanisms to discover and inventory AI identities, including:
o AI models, agents, and autonomous workflows
o Service accounts, non-human identities, and API principals used by AI systems
o Identities created dynamically through AI pipelines, orchestration tools, and integrations
• Maintain authoritative visibility into where AI identities exist, what they can access, and how they are used across environments.• Integrate AI identity discovery into broader identity, asset, and AI Security Posture Management (AI-SPM) capabilities.
AI Identity Lifecycle Management• Define and operationalize lifecycle controls for AI identities, including creation, modification, rotation, suspension, and decommissioning.• Ensure AI identities are created with strong provenance, ownership, and accountability, including linkage to business and technical owners.• Implement controls to prevent identity sprawl, orphaned AI identities, and unmanaged credentials.
Access Control & Policy Enforcement• Design and enforce least-privilege access models for AI identities, aligned with the sensitivity of data, models, and actions performed.• Partner with IAM and platform teams to implement policy-based access controls, including role-based, attribute-based, and context-aware authorization for AI systems.• Ensure AI identities comply with enterprise security standards for authentication strength, credential handling, and key/token management.
Monitoring, Detection & Risk Assessment• Implement continuous monitoring of AI identity behavior, including access patterns, privilege use, and anomalous activity.• Detect and investigate identity-based risks and threats, such as excessive permissions, credential misuse, lateral movement, or abuse of AI agents.• Leverage telemetry from identity platforms, cloud providers, and AI security tools to assess ongoing AI identity risk.
AI Security Assessments & Control Validation
• Conduct security assessments focused on AI identity usage, including architecture reviews, threat modeling, and control effectiveness testing.• Validate that AI identity controls are correctly implemented and enforced across development, testing, and production environments.• Partner with engineering teams to remediate identified gaps and track risk reduction over time.
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