Background

Trusted Research and Real World-Data Utilisation and Sharing Tech (TRUST) is a national data governance framework and analytics platform that enables the safe, secure and responsible use of research and real-world datasets. It helps researchers unlock insights that advance innovation, improve health outcomes and benefit society. www.trustplatform.sg

As AI capabilities evolve rapidly - from classical machine learning to Agentic AI system – TRUST needs to anticipate how these developments will reshape research workflows, what new risks they introduce, and how TRUST infrastructure, processes and governance must evolve to support them safely and effectively. TRUST's AI roadmap includes strengthening AI lifecycle governance, enabling safe model sharing, supporting federated and privacy-preserving analytics, and preparing for emerging AI technologies.

This role sits at the intersection of AI technology, strategic planning and implementation. The successful candidate will have a working understanding of how AI systems are built and deployed and will use that technical grounding to engage meaningfully with researchers, clinicians, data scientists, industry partners and regulatory bodies on technical and governance matters. The individual will coordinate and synthesise technical and operational perspectives, interrogate technical assumptions, assess implications and translate them into practical plans, frameworks and operational guardrails that enable innovation within trusted research environments and broader national data ecosystems rather than hinder it, without compromising data privacy or security.

The role is ideally suited for someone who has been involved in the actual doing – whether in AI model development, evaluation or deployment in regulated or research setting to bring that experience to bear on planning and governance challenges for TRUST.

Key Responsibilities

Support AI Strategic Planning and Coordinate Technology Foresight

• Maintain awareness of responsible AI practice, governance and regulatory developments locally and internationally, drawing on internal and external expertise (e.g. AI research community, regulatory bodies etc).
• Translate above insights into recommendations that ensure TRUST infrastructure, governance and operational capabilities evolve in step with emerging AI use cases and deployment paradigms.
• Coordinate the assessment of emerging AI technologies with TRUST’s technology team, researchers and advisors where relevant.

Support AI Governance and Risk Frameworks

• Support the development of governance frameworks across the whole lifecycle from training, evaluation, validation, deployment, monitoring, and sharing of AI models.
• Support translation and implementation of these governance frameworks such as model documentation, model cards, validation evidence, auditability, monitoring, and lifecycle management.
• Identify and develop risk-tiered approaches to address data privacy and cybersecurity risks introduced by emergent AI technologies and work with relevant teams and experts to develop practical mitigations.

Co-Shape Use Cases and Governance Through Practice

• Partner directly with researchers, public agencies, industry collaborators and AI practitioners to co-develop high-impact, real-world AI projects that serve as testbeds for balancing innovation with the scalability and effectiveness of TRUST’s governance approaches, workflows and operational guidance.

• Identify implementation challenges, operational bottlenecks, and unintended consequences early, and translate lessons into improved implementation practices and guides that can be adopted across multiple programmes and institutions.

Job Requirements

• Degree in Computer Science, Data Science, Health Informatics, Biomedical Informatics, Engineering, Public Policy, Law, or a related discipline.
• 7-10 years of relevant experience spanning AI development or implementation, healthcare analytics or digital health, technology strategy, or AI governance
• Working understanding of AI concepts, machine learning and AI development lifecycles and familiarity with AI privacy, security risks and mitigations.
• Hands-on experience in at least one of the following: AI model evaluation, model sharing, lifecycle monitoring, or deployment of AI solutions in regulated or research settings.
• Experience working with researchers, clinicians, data scientists, or technology teams to deploy AI solutions in real-world settings. Familiarity with large language models, foundation models, frontier models or agentic AI systems is highly advantageous.
• Ability to engage both technical and non-technical stakeholders, interrogate technical assumptions and translate between policy and implementation perspectives.

Success in the Role

Success will be measured by the quality of the role-holder’s strategic thinking, usefulness of the insights and recommendations produced, and tangible improvements that these enable across TRUST.  The right individual will have helped TRUST to:

• Anticipate emerging AI developments and assess their implications before they become immediate governance and operational issues.
• Anticipate and support the development of governance frameworks and operational readiness for emerging AI use cases.
• Support the establishment of AI governance frameworks that are trusted, practical, enabling and scalable.
• Enable safe adoption of AI in the TRE and in research and healthcare deployment settings.
• Balance innovation, public benefit, and risk management to build trust
• Position TRUST as a national leader in responsible AI development, evaluation, deployment, and sharing using real-world and research data.