Role Summary:
Lead the implementation of AI Security and AI Governance practices by ensuring Artificial Intelligence (AI) systems are designed, deployed, and managed securely while complying with organizational policies, regulatory requirements, and international standards. Support secure adoption of AI technologies by identifying AI-related risks, implementing security controls, and establishing governance frameworks across the AI lifecycle.
Key Responsibilities:
- Develop, implement, and continuously improve the organization's AI Security and Governance Framework.
- Define AI security policies, standards, procedures, and operational guidelines.
- Establish AI governance processes aligned with business objectives and regulatory requirements.
- Conduct AI risk assessments and identify security, privacy, ethical, and operational risks associated with AI solutions.
- Perform AI threat modeling and security architecture reviews.
- Evaluate AI systems throughout the lifecycle, including design, development, deployment, monitoring, and retirement.
- Review AI models for robustness, explainability, fairness, transparency, and resilience.
- Assess AI solutions against organizational risk appetite and governance requirements.
- Support implementation of Responsible AI principles across business and technology teams.
- Perform security assessments of AI applications, machine learning models, and Generative AI platforms.
- Assess AI model risks, including prompt injection, model poisoning, adversarial attacks, data leakage, model theft, and unauthorized access.
- Review AI data pipelines and model training datasets from security and privacy perspectives.
- Conduct security assessments for third-party AI platforms and AI service providers.
- Ensure AI solutions comply with ISO/IEC 42001, ISO/IEC 27001, ISO/IEC 27701, NIST AI Risk Management Framework (AI RMF), and applicable banking regulations.
- Support AI governance audits and regulatory assessments.
- Review AI-related policies, procedures, and technical standards.
- Develop AI risk registers and maintain AI asset inventories.
- Define AI-specific security controls and monitoring mechanisms.
- Review AI incident response procedures and participate in AI security investigations.
- Monitor AI-related vulnerabilities and emerging threats.
- Collaborate with Cyber Security, Architecture, Risk, Privacy, and Development teams to implement AI security controls.
- Recommend AI governance tools and AI security solutions.
- Prepare executive dashboards, risk reports, and compliance metrics.
- Deliver AI security awareness sessions and technical guidance to stakeholders.
- Stay updated on emerging AI regulations, standards, and industry best practices.
Technical Skills:
- AI Security & AI Governance
- ISO/IEC 42001
- ISO/IEC 27001 & ISO/IEC 27701
- NIST AI Risk Management Framework (AI RMF)
- AI Risk Assessment & Threat Modeling
- Generative AI & LLM Security
- Secure AI/ML Lifecycle (MLOps)
- AI Privacy & Data Protection
- Cloud Security (Azure, AWS, Oracle Cloud)
- Identity & Access Management (IAM)
- API Security
- Security Architecture
- Vulnerability Management
- Data Classification & Protection
- GRC & Regulatory Compliance
Qualifications & Experience
- 6–10 years of experience in Cyber Security, Information Security, AI Security, or Security Architecture.
- Minimum 3 years of hands-on experience in AI Security, AI Governance, or AI Risk Management.
- Experience implementing AI security controls within enterprise environments.
- Strong understanding of AI/ML technologies, Large Language Models (LLMs), and Generative AI security risks.
- Banking or Financial Services experience preferred.
- Experience with enterprise AI platforms such as Microsoft Copilot, Azure OpenAI, OpenAI, Google Vertex AI, AWS Bedrock, or Oracle AI services is preferred.
- Bachelor's degree in computer science, Information Security, Artificial Intelligence, Data Science, or a related field.
