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# Enterprise Architect IAM

- **Company:** Tata Consultancy Services Limited
- **Location:** Irvine, CA, United States
- **Experience:** Expert
- **Salary:** $120,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Cloud Computing, Cloud Computing Security, Cyber Security, Information Leak Prevention, Identity and Access Management, Information Systems Security Architecture Professional, Role-Based Access Control, Zero Trust Network Access, Enterprise Software Applications, Cloud Platform System, Multi-Agent Systems, Multi-Cloud, AI Platforms, Kubernetes, Information Technology, Bots, Enterprise Integration, Machine Learning Operations, Data Pipelines, Automation Anywhere
- **Published:** May 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bcf484be6e7b6bb7

## About the Role

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

 3. Responsibilities
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Define and drive a unified enterprise IAM and security architecture spanning cloud platforms, applications, SOC tooling, AI platforms, and automation workflows., Qualifications : BACHELOR OF COMPUTER SCIENCE
You must create an Indeed account before continuing to the company website to apply

## Description

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


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