[What the role is]

Overall Job Purpose
The Assistant Manager, Data & AI is responsible for the hands-on engineering, deployment, and operational health of Sentosa Development Corporation's (SDC) Data & AI applications and underlying infrastructure. The role contributes towards building and deploying AI products across guest-facing and staff-facing use cases, automates data ingestion and pipeline operations, and serves as the technical liaison for whole-of-government (WOG) security assessments and IT governance processes. The role works closely with the AI Engineering lead, business stakeholders, vendors, and SDC's IT department to ensure AI products and data platforms are reliable, secure, and aligned to WOG standards.

[What you will be working on]

Key Responsibilities

AI Application Development

•     Execute the roadmap for AI applications spanning guest experience, staff productivity, and corporate process augmentation, including conversational assistants, retrieval-augmented generation systems, and purpose-built AI tools.

•     Lead the development of AI-assisted decision support tools for corporate and operational processes, from prototype through to pilot deployment and adoption.

•     Contribute engineering effort across the full AI applications portfolio, including agentic systems and data-driven capabilities, with clear modular ownership and knowledge transfer.

Data Infrastructure and Pipelines

•     Design, build, and maintain enterprise data pipelines that ingest, transform, and load data from operational systems into the central data platform, ensuring reliability, accuracy, and scalability.

•     Drive automation of manual data ingestion processes to reduce operational workload and improve data freshness and quality.

•     Maintain the health of the enterprise data platform, including cloud data warehouse and analytics environments, with monitoring, performance tuning, and cost optimisation.

Security and WOG Governance Liaison

•     Serve as the technical liaison with SDC's IT department and external security partners for whole-of-government security assessments, including vulnerability assessments and penetration testing (VAPT) on Data & AI systems.

•     Coordinate quarterly security review cycles, remediate findings within agreed service levels, and maintain a documented security posture for all Data & AI products and infrastructure.

•     Ensure all Data & AI engineering work complies with IM8, WOG data governance, and other applicable standards, including alignment to SGTS-approved tooling and government commercial cloud requirements.

Stakeholder and Vendor Engagement

•     Engage business stakeholders to translate requirements into engineering deliverables, with clear scoping, estimation, and post-delivery support.

•     Manage AI and data engineering vendors against project milestones, technical quality, and contractual commitments.

[What we are looking for]

Job Requirements

Qualifications and Experience

•     Master's or Bachelor's degree in Computer Science, Engineering, Data Science, or related discipline.

•     3-5 years of progressive experience in data engineering, software engineering, or AI application development, including hands-on delivery of production systems.

•     Demonstrated experience building and operating cloud-based data pipelines and AI applications, with familiarity in widely used enterprise data warehouse platforms (e.g. Snowflake, MSSQL databases)

•     Experience with WOG digital policies, government commercial cloud environments, IM8 requirements, and security review processes is an advantage.

Knowledge, Capability, and Attributes

•     Strong technical depth in data engineering, including SQL and NoSQL databases, ETL/ELT pipeline design, and modern data orchestration tools.

•     Working knowledge of Full stack development for AI applications & knowledge of architecture including LLMs, retrieval-augmented generation, vector databases, and prompt engineering.

•     Practical experience with cloud-native development, CI/CD pipelines, containerisation, and infrastructure-as-code.

•     Sound understanding of IT security principles, vulnerability management, and the practical execution of security assessments.

•     Strong problem-solving instincts, ability to work across multiple parallel workstreams, and a proactive approach to learning new technologies.