Join NTT DATA as an Enterprise Security Architect focused on Agentic AI Platform Security in Bangalore. This senior, hands-on role involves owning the security architecture and risk posture for our cutting-edge Agentic AI platforms. You will operate at the intersection of enterprise security, cloud security, and emerging AI/LLM security disciplines.

Your expertise will be crucial in designing robust security controls, reference architectures, and governance frameworks. These will enable the safe, scalable, and compliant deployment of agentic AI technologies, including LLM agents and autonomous workflows, aligning with regulatory and internal risk requirements.

Key responsibilities include designing end-to-end security for agentic AI platforms, covering agent orchestration, tool integrations, model endpoints, and inter-agent communication. You will define secure patterns for tool usage, function calling, and API access, while establishing robust identity and access models for non-human identities.

Furthermore, you'll architect guardrails against sophisticated threats like prompt injection and data exfiltration, and design secure patterns for RAG and vector databases. Building AI security risk frameworks aligned with standards like OWASP Top 10 for LLM Applications, and partnering with GRC, Legal, and Privacy teams to ensure regulatory compliance are also core functions. Operational security, including monitoring, logging, and incident response for agentic AI, alongside cloud and network security for AI workloads, will be central to this role.

We are seeking candidates with over 10 years in security architecture, application security, or cloud security, including enterprise-scale environments. A minimum of 3 years of hands-on experience securing AI/ML or LLM-based systems, with direct exposure to agentic architectures, is essential.

Strong knowledge of LLM-specific threat models, agentic AI frameworks (e.g., LangChain, AutoGen), and deep expertise in identity and access management, cloud security architecture (AWS/Azure/GCP), container and Kubernetes security, and API security are required. Solid network security fundamentals, experience with cloud landing zones, and securing data-in-transit are also critical. Familiarity with AI security frameworks and regulations, along with excellent communication skills to translate technical risks into business terms, is expected.