Lead AI Security Architect (Ref 26289)

Responsibilities
• Collaborate with Group Security and Data Governance teams to align AI platform designs with enterprise security and compliance policies. 
• Define and implement secure-by-design architectural principles for AI/ML platforms, covering data pipelines, model deployment, and access layers. 
• Implement and oversee Responsible AI (RAI) practices to ensure AI systems are designed and deployed ethically, with fairness, transparency, and compliance 
• Implement and oversee Explainable AI (XAI) practices to ensure AI model decisions are transparent, interpretable, and trustworthy through integrated explainability features. 
• Ensure compliance with regulatory frameworks and AI governance standards. 
• Ensure secure and compliant architecture in collaboration with cybersecurity and governance teams, embedding PDPA and enterprise policy requirements into designs 
• Translate governance requirements into technical specifications and enforceable controls across cloud and on-premise AI environments. 
• Integrate privacy-preserving mechanisms such as data anonymization, encryption, tokenization, and secure logging into AI workflows. 
• Evaluate and recommend AI security and governance tools (e.g. AWS Guardrails, Azure Responsible AI, IBM Watson Governance) for adoption. 
• Conduct AI-specific risk assessments, including model misuse, bias, data leakage, adversarial attacks, and LLM prompt vulnerabilities. 
• Review and approve the integration of third-party AI services and open-source models from a security and compliance perspective. 
• Champion awareness of AI security and governance across AIDA by contributing to policies, best practices, and team enablement sessions. 
• Review and clear governance approvals related to architecture and solution design, with specific focus on AI security. 
• Collaborate with vendors and partners to review, evaluate, and select appropriate security solutions. 
• Ensure all AI solutions, including in-house and vendor-developed systems, undergo thorough testing and Vulnerability Assessment and Penetration Testing (VAPT) to safeguard security and reliability. 

Requirements
• Bachelor’s or Master’s degree in Cybersecurity, Engineering, AI/ML, or related field. 
• More than 5 years of experience in cybersecurity, data governance, or secure systems architecture, with at least 3 years focused on AI or cloud-based ML systems 
• Proven expertise in implementing cybersecurity governance, data protection, etc on data or AI platform. 
• Strong understanding of AI/ML pipeline components and risks—model misuse, prompt injection, data leakage, adversarial inputs, bias and explainability. 
• Proficient in implementing secure and compliant AI/ML systems on cloud platforms such as AWS SageMaker, Azure ML, Google Vertex AI, etc. 
• Experience with AIOps/LLMOps and DevSecOps practices, including secure CI/CD, RBAC, secrets management and logging 
• Familiarity with AI governance toolkits and regulatory trends 
• Technical knowledge of data privacy controls (encryption, tokenization, data minimization) and security frameworks (e.g., Zero Trust, OWASP for ML)     
• Ability to perform threat modeling and security assessment for AI and LLM-based systems 
• Strong cross-functional communication and collaboration skills, with the ability to influence both technical and policy-level decisions  
• Good internal (IT, Networks, business) and external (suppliers, government) stakeholders management skills  
• Strong technical writing and presentation skills, with the ability to communicate complex concepts clearly to both technical and non-technical stakeholders.   
• Proactive and fast learner with a strong drive to stay current on emerging technologies and industry trends   
• Proven experience working in a telco environment or implementing security and governance role is a plus 

Licence no: 12C6060