Ai Security Architect Job at NTT DATA (Bangalore)

Job Description

We are currently seeking a AI Security Architect to join our team in Bangalore or Remote, Karnātaka (IN-KA), India (IN). Role: AI Security Architect. PAN India (Bangalore, Hyderabad, Chennai, Noida, Gurgaon and Pune). Notice Period: 30 Days.

Job Responsibility

Defining security architecture and implementing robust security controls for AI/ML systems and their underlying platforms
Serving 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)
Proactively mitigating AI-specific threats such as model integrity risks, data poisoning, adversarial attacks, prompt injection, model extraction, and inference-time abuse
Leading technically, setting standards, and guiding engineers day-to-day through architecture, reviews, and delivery
Ensuring AI systems are secure, compliant, and resilient by implementing data protection, threat detection, guardrails, and ongoing risk monitoring across the AI lifecycle
Agent Security: Define strict Role-Based Access Control (RBAC) and least-privilege models for AI agents
Design runtime environments with restricted permissions
Implement defenses against adversarial attacks, prompt injections, jailbreaking, and sensitive data leakage (DLP) across agent workflows
Observability & Monitoring: Architect logging and monitoring standards for decision traceability
Monitor models and prompt templates for behavioral drift, anomalies, and attacks
SOC Monitoring & Automation: Design LLM-driven and agentic workflows for alert triage, contextual correlation, false-positive filtering, and playbook automation
Establish remediation strategies and threat-hunting procedures
Compliance Enablement & Governance: Map AI-specific controls to NIST AI RMF, OWASP Top 10 for LLMs, and GDPR
Build audit pipelines for regulatory compliance
Architecture & Secure-by-Design Leadership: Define and maintain AI security reference architectures
Establish and evolve security requirements, patterns, and guardrails across the AI/ML SDLC
Own AI security architecture decisions across identity, secrets, data protection, network controls, tenancy boundaries, logging/telemetry, and isolation
Control Design & Implementation (Hands-on): Design and deploy controls for model integrity and governance
Build technical mechanisms for provenance, attestation, signing, and approval workflows
Drive implementation of runtime protections
Threat Modeling, Assurance, and Risk Reduction: Conduct and lead AI/ML-specific threat modeling
Define and run security design reviews
Establish AI security testing approaches
Tooling, Automation, and Operational Enablement: Design and deliver AI security tooling
Define logging/monitoring standards and detection use-cases
Technical Mentorship & Influence: Act as the team’s technical mentor
Lead by influence across Data Science, Engineering, Product, Platform, and Cybersecurity
Create internal enablement materials

Requirements

5+ years in cybersecurity architecture with proven experience securing large-scale LLM deployments and multi-agent workflows
Hands-on capability with agent frameworks (e.g., LangChain, LangGraph, AutoGen) and MLOps platforms
Deep familiarity with model risk management principles and AI security standards

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Ai Security Architect

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