The candidate will be responsible for designing and developing AI-powered solutions and agents for cybersecurity use cases, establishing AI security guardrails, implementing AI governance frameworks, managing AI risks, ensuring regulatory compliance, and securing enterprise AI platforms.

The ideal candidate should be capable of both writing code and building AI agents while simultaneously acting as the organization's subject matter expert for AI security, responsible AI, compliance, and governance.

Reporting To Head - Cybersecurity / CISO

Experience

- 10-15 years overall Cybersecurity experience.
- Minimum 3+ years hands-on experience in AI/GenAI engineering.
- Proven experience developing AI agents and AI applications.
- Experience establishing AI governance programs.
- Hands-on coding experience in Python and AI frameworks.
- Experience securing enterprise AI deployments.

Preferred

- Experience within critical infrastructure, ports, logistics, manufacturing, utilities or energy sectors.
- Experience with OT/ICS environments.
- Experience implementing ISO 42001 programs.

Key Responsibilities AI Security Engineering & Innovation

Design, develop, deploy, and maintain AI agents, copilots, and GenAI applications for cybersecurity operations.

- Build AI-enabled use cases across:
- SOC Operations
- Threat Hunting
- Incident Response
- Vulnerability Management
- Threat Intelligence
- Security Automation
- Identity Security
- OT/ICS Security
- Develop Agentic AI solutions integrating enterprise security tools.
- Implement AI orchestration frameworks using:
- LangChain
- LangGraph
- Semantic Kernel
- MCP Servers
- Azure AI Foundry
- Google Vertex AI
- OpenAI APIs




- Build RAG-based solutions using enterprise knowledge repositories.
- Develop custom AI models, assistants, and security copilots for cyber teams.

AI Security & Guardrails Define and implement enterprise-wide AI security controls and guardrails.

- Secure AI platforms against:

- Prompt Injection

- Jailbreak Attacks

- Data Leakage

- Model Poisoning

- Supply Chain Risks

- Unauthorized Data Access

- Can Implement:

- Model Armor

- AI Firewalls

- AI Security Monitoring

- AI Access Controls

- DLP Controls

- Content Filtering Mechanisms
- Conduct AI Red Teaming and Adversarial Testing exercises.
- Establish AI security architecture standards.

AI Governance & Compliance Establish and operationalize enterprise AI Governance Framework.

- Define AI policies, standards and procedures.
- Maintain AI inventory, AI asset register and use case register.
- Perform AI risk assessments and DPIA-like reviews.

- Ensure compliance with

- ISO/IEC 42001

- NIST AI RMF

- DPDP Act

- Responsible AI Guidelines

- Group AI Governance Requirements
- Implement AI model lifecycle governance.
- Define approval workflows for AI use cases.

Risk Management & Assurance Conduct AI risk assessments for all AI initiatives.

- Develop AI risk taxonomy and control frameworks.




- Review third-party AI solutions from a security and compliance perspective.
- Assess AI vendors and AI-enabled SaaS solutions.
- Drive AI security audits and compliance reviews.
- Maintain AI risk register and remediation tracking.

AI Operations & Monitoring

- Establish AI Security Operations capabilities.
- Monitor AI agent activities and model usage.
- Define AI-specific metrics and KPIs.

- Implement

- AI Logging

- AI Observability

- AI Drift Monitoring

- Model Monitoring

- Abuse Monitoring
- Develop dashboards for executive reporting.

Enterprise Enablement

- Act as the central AI Security SME across all business units.
- Guide development teams on secure AI implementation.
- Conduct AI security and governance training programs.
- Support AI innovation initiatives while ensuring compliance.
- Collaborate with legal, privacy, risk, audit and technology teams.

Success Metrics (First 12 Months)

- Establish Enterprise AI Governance Framework.
- Create and operationalize AI Security Standards.
- Develop at least 20 enterprise AI/Cyber AI agents.
- Implement AI risk assessment process across all AI use cases.
- Establish AI Security Review Board.
- Achieve ISO/IEC 42001 readiness.
- Deploy AI security monitoring and guardrails.
- Reduce manual SOC effort through AI-driven automation.
- Launch enterprise-wide responsible AI program.

A hands-on AI engineer with solid cybersecurity expertise who can build AI agents, develop AI-powered cyber use cases, secure enterprise AI deployments, and drive AI governance can email at [email protected] OR reach at (phone hidden)

📌 Lead AI Security & Governance Architect (Mumbai)
🏢 Adani Group
📍 Mumbai