Build and scale solutions, embedding new ways of working, driving adoption, managing risk, and ensuring AI is deployed responsibly and effectively in a way that improves both outcomes and operating models.
Represent Singapore and/or IMDA at relevant research and technology forums and standards setting committees. Establish IMDA’s thought leadership in AI and Trust Technologies in blogs, social media and papers.
・Work with clients from the early stage: understand their business, define requirements, and translate the "what" into the "how" (architecture, technology choices, scope, and estimates).
Champion rapid experimentation, prototyping and iterative development, using modern AI-assisted and vibe-coding approaches where appropriate to shorten development cycles
Establish architectural best practices for AI model deployment, evaluation, versioning, monitoring, retraining, performance optimisation and retirement. Drive the adoption of enterprise AI patterns, including RAG, agentic AI, workflow orchestration and API integrations.
Work with clients and senior teammates to analyze business challenges, map workflows (service blueprints) to better understand customer journey in order to identify gaps and opportunities for AI/ML use cases.
The Data Engineer designs, builds and maintains data pipelines, integrations and data structures that support AI, machine learning, analytics and automation solutions. The role works with approved enterprise data platforms, including Databricks and Microsoft Fabric (medallion architecture), to ensure data is reliable, secure, well-governed and ready for approved technical and business use cases.