Our Client is seeking an AI Lead/Agentic Identity Engineer .

Responsibilities:

• Define the enterprise target-state architecture for AI agent identity, authorization, governance, and auditability
• Design the operating model for treating agents as governed non-human identities, including ownership, lifecycle, registration, approval, attestation, recertification, and retirement
• Create reusable reference architectures for agent onboarding, delegated access, tool invocation, runtime policy enforcement, and end-to-end attribution
• Lead design of agent identity patterns across IdPs, CI/CD pipelines, agent build platforms, secrets management, API gateways, service meshes, and cloud-native workload identity services
• Develop implementation blueprints for cryptographic workload identity, including SPIFFE/SPIRE or equivalent patterns, mTLS, short-lived credentials, certificate-based authentication, and key lifecycle controls
• Define authorization patterns for OAuth 2.0/2.1, OIDC, token exchange, on-behalf-of flows, audience-bound tokens, just-in-time access, and delegated authority in agentic workflows
• Establish architecture principles for Model Context Protocol, Agent2Agent, multi-agent orchestration, and tool-calling systems, including no token pass-through, bounded delegation, and least-privilege tool access
• Design policy decision and enforcement models that apply consistently from edge to API to service to AI runtime layers
• Guide implementation of runtime guardrails for high-risk actions, including step-up controls, human-in-the-loop approvals, revocation, rate limits, transaction thresholds, and emergency stop patterns
• Partner with security engineering teams to align agent identity architecture with Zero Trust, privileged access management, secrets management, vulnerability management, and detection engineering capabilities