Enterprise Architect - Security & IAM

Job Description
Enterprise Architect - Security & IAM
Experience Required: 10-16 years overall IT experience; 5-7+ years in security architecture and IAM/IGA/PAM; strong regulatory/compliance experience


1. 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.


2. 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

• 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.