
Lead AI Security & Governance Specialist
- Singapore
- Permanent
- Full-time
- Collaborate with Singtel's 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.
- 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.
- 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 MLOps 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 modelling 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.
- Full suite of health and wellness benefits
- Ongoing training and development programs
- Internal mobility opportunities