AIA Digital+ is a Technology, Digital and Analytics innovation hub dedicated to powering AIA to be more efficient, connected and innovative as it fulfils its Purpose to help millions of people across Asia-Pacific live Healthier, Longer, Better Lives.

If you are hungry and driven to play an active role in shaping a better tomorrow, we want to hear from you. Because the work we do at AIA Digital+ makes a difference in the lives of millions of people, every day. We will equip you with the critical skills, tools and technology, and endless opportunities to learn, contribute and thrive in a dynamic and exciting environment.

If you want to shape a brighter future at AIA Digital+, please read on.

About the Role

Enable datadriven, AIpowered transformation by translating business problems into measurable AI use cases, validating feasibility and value, and supporting endtoend delivery-from data readiness and model evaluation through pilot, scaleup, and adoption. This role supports the organization's digital transformation by exploring emerging AI capabilities, building prototypes and implementation, and managing AI-driven workflows to enhance automation and efficiency within group applications operations.

• Conduct structured assessments of business processes to identify AI automation, augmentation, and analytics opportunities (e.g., classification, forecasting, NLP, computer vision, generative AI).
• Identify gaps and mitigation plans (data enrichment, labeling strategies, synthetic data considerations).
• Define and track performance, robustness, fairness, and safety metrics (accuracy, latency, drift, bias, hallucination rates).
• Coordinate UAT and pilot execution collect qualitative/quantitative feedback and iterate with the team.
• Support deployment readiness: monitoring plans, incident processes, rollback criteria, and performance dashboards.
• Ensure solutions comply with internal policies and jurisdictional regulations (privacy, DLP).
• Maintain usecase backlogs and documentation repositories.
• Produce simple insights, summaries, and visualizations to support AI experimentation and decisionmaking.
• Contribute to prompt engineering, test cases, or evaluation templates where applicable.
• Support user acceptance testing (UAT), pilot tracking, and feedback collection.
• Help document model performance results against defined metrics (e.g., accuracy, response quality, turnaround time).
• Assist in preparing required documentation such as usecase briefs, data summaries, and basic model documentation.
• Maintain versioned artifacts, decision logs, and auditready documentation.
• Stay current on foundational AI concepts, tools, and platforms used within the organization.
• Participate in internal training, communities of practice, and continuous improvement initiatives.
• Demonstrate strong attention to detail, accountability for assigned tasks, and willingness to learn.