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You apply directly with the employer. We never charge applicants.
Singapore
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[What the role is]
Job Description Summary[What you will be working on]
Job Description
Key Responsibilities
• 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.
• 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.
• 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.
• 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]
• 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.
• 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.