AI Security Architect

Req : 375676

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a AI Security Architect
- Dallas onsite to join our team in Dallas, Texas (US-TX), United States (US).

AI Security Architect (Agent Security, Observability, SOC Monitoring & Compliance Enablement)

Dallas Texas / onsite

10 + years

We are seeking an experienced and highly skilled AI Security hands-on, highly technical architect responsible for defining security architecture and implementing robust security controls for our AI/ML systems and their underlying platforms and will serve as the team’s technical mentor and architecture authority
, driving secure-by-design patterns across the AI/ML lifecycle (data, training, evaluation, deployment, and production monitoring) and proactively mitigating AI-specific threats such as model integrity risks, data poisoning, adversarial attacks, prompt injection, model extraction, and inference-time abuse
. L ead technically
, set standards, and guide engineers day-to-day through architecture, reviews, and delivery.

Ensures AI systems are secure, compliant, and resilient by implementing data protection, threat detection, guardrails, and ongoing risk monitoring across the AI lifecycle.

• AI Platform Admin (M365, copilot Studio) Manages AI platforms and environments, including access provisioning, governance controls, and policy enforcement (e.g., DLP, security, and compliance).

• AI Reusable Utility Develops reusable components (e.g., prompts, connectors, APIs, templates) to accelerate AI solution delivery and promote standardization across use cases.

• AI Common Infrastructure, Framework & Observability Architect (AWS and Azure) Designs and maintains the foundational AI infrastructure, frameworks, and observability capabilities (telemetry, monitoring, metrics) required for scalable, reliable, and governed AI operations.

Agent Security

• Non-Human Identity & Access: Define strict Role-Based Access Control (RBAC) and least-privilege models for AI agents using identity systems (e.g., Entra Agent ).

• Guardrails & Sandboxing: Design runtime environments with restricted permissions to prevent manipulated agents from accessing unauthorized APIs, data sources, or executing malicious tool chains.

• Input/Output Protection: Implement defenses against adversarial attacks, prompt injections, jail breaking, and sensitive data leakage (DLP) across agent workflows.

Observability & Monitoring

• Decision Traceability: Architect logging and monitoring standards to map how reasoning agents use data and call APIs, eliminating "black box" decisions.

• Model Drift & Integrity: Monitor models and prompt templates in production to detect behavioral drift, anomalies, and poisoning or evasion attacks.

SOC Monitoring & Automation

• Autonomous Security (AI SOC): Design LLM-driven and agentic workflows to improve alert triage, contextual correlation, false-positive filtering, and playbook automation.

• Incident Response Playbooks: Establish remediation strategies and threat-hunting procedures for AI-specific events (e.g., compromised model artifacts, hallucination-driven exploits).

Compliance Enablement & Governance

• Regulatory Alignment: Map AI-specific controls to established standards like the NIST AI RMF, OWASP Top 10 for LLMs, and GDPR.

• Audit Readiness: Build audit pipelines that track and explain everything an agent does to satisfy ongoing AI regulatory compliance and governance requirements.

Architecture & Secure-by-Design Leadership

• Define and maintain AI security reference architectures for multiple AI deployment patterns, including MCP / Agentic AI and LLM application stacks (RAG, tools/plugins, agents, orchestration).

• Establish and evolve security requirements, patterns, and guardrails across the AI/ML SDLC (design → build → run), including secure pipelines and platform controls.

• Own AI security architecture decisions across critical domains:
  identity, secrets, data protection, network controls, tenancy…