Enterprise Architect – Security & IAM

Enterprise Architect – Security & IAM

Location:

Irvine, CA FTE

Experience

Required:

10–16 years overall IT experience; 5–7+ years in security architecture and IAM/IGA/PAM; strong regulatory/compliance experience

Background

In addition to traditional enterprise security and IAM responsibilities, this role addresses the rapid expansion of AI-driven and agentic systems across the enterprise. As AI agents, automation, and non-human identities increasingly interact with cloud platforms, enterprise applications, and sensitive data, the role ensures that identity, access, and security governance extend consistently across human, non-human, and agentic actors. The architect plays a key role in defining secure, auditable, and governed adoption of AI and agentic workflows, aligned with enterprise security strategy and regulatory expectations.

Skills Required

• Strong experience in enterprise security architecture, Zero Trust principles, and security-by-design across hybrid and multi-cloud environments
• Ability to define security architectures that integrate IAM, SOC, and platform security controls into a cohesive enterprise model
• Deep expertise in IAM concepts: authentication, authorization, federation, lifecycle management, and privileged access
• Strong understanding of non-human identities (NHIs) including service accounts, API keys, workload identities, bots, and AI agents
• Experience defining IGA and PAM patterns that scale beyond human users to machine and agent identities
• Understanding of agentic AI security challenges, including delegated authority, autonomy, and post-authentication risk
• Experience designing identity-first security models for AI agents acting across multiple systems and platforms
• Familiarity with governance models for AI agents as first-class identities, including ownership, least privilege, and auditability
• Knowledge of Security for AI: protecting AI systems, models, agents, and data pipelines from misuse, over-permissioning, and data leakage
• Knowledge of AI for Security: applying AI/ML to enhance detection, identity risk analysis, and security operations (conceptual/architectural level)
• Awareness of Model Context Protocol (MCP) as an emerging AI-to-enterprise integration standard and its security implications
• Understanding of MCP governance needs: scoped access, tool authorization, audit trails, ownership, and runtime controls
• Ability to define enterprise-wide governance models covering cloud, SOC, IAM, AI workflows, and agentic systems
• Strong experience collaborating with risk, compliance, audit, and security leadership in regulated environments

Responsibilities

• Define and drive a unified enterprise IAM and security architecture spanning cloud platforms, applications, SOC tooling, AI platforms, and automation workflows.
• Establish identity and access strategy for both human and non-human identities, including applications, APIs, service accounts, bots, agents, and AI workloads.
• Architect IAM for the agentic and AI-driven world, covering AI agents, orchestration frameworks, MCP-style patterns, and autonomous workflows.
• Define security guardrails for AI systems (Security for AI), including identity controls, access boundaries, auditability, and governance across AI pipelines and agent interactions.
• Enable AI-driven security capabilities (AI for Security) by guiding integration of AI into detection, monitoring, identity risk analysis, and SOC workflows.
• Establish governance models for non-human and agent identities, including lifecycle management, least-privilege access, approval workflows, and continuous review.
• Define enterprise standards and reference architectures for IAM, IGA, PAM, RBAC/ABAC, and non-human IAM across hybrid and multi-cloud environments.
• Ensure IAM and security architectures align with Zero Trust principles, regulatory requirements, and internal security policies.
• Partner with security leadership, SOC, cloud, data, and AI platform teams to ensure consistent identity enforcement across security operations and AI workflows.
• Provide architectural guidance and design review support for initiatives involving cloud security, IAM modernization, AI platforms, and automation, without assuming delivery ownership.
• Produce clear, executive-ready security and IAM architecture artifacts, including target-state diagrams, standards, and roadmap recommendations.