AI Data Architecture

Hong Kong·Hk-Aia Hong Kong & Macaumid

OtherArchitecture

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Quick Summary

Key Responsibilities

Develop AI data architecture strategies, best practices, and standards for GenAI / AI usecases. Create data architecture strategies and roadmap for GenAI / AI platforms and technology stacks.

Technical Tools

OtherArchitecture

As pioneering innovators for over 100 years, we’re now transforming our organisation to be faster, simpler and more connected. Because we want to be even better equipped to develop digital solutions and experiences that help more people live Healthier, Longer, Better Lives.

To get there, we need people with tech/digital/analytics expertise and passion to help develop positive, sustainable change through digitally enhanced experiences that will impact the lives of millions of people and create a healthier future for everyone.

About the Role

~1 min read

Position Objective: The Data Science Lab COE and Transformation team at AIA HK deliver advanced AI solutions, including GenAI usecases, AI ML models, ML engineering and data science platform, to our customers, agents, partners and Healthcare providers.

As an AI Data Architect, this role will be to design and implement data architectures optimized for cloud platforms and AI/ML workloads for the Data Science Lab COE and Transformation team. The AI Data Architect will leverage cutting-edge technologies, cloud infrastructure, and AI-driven approaches to build scalable, secure, and high-performance AI data ecosystems. These solutions utilize an integrated AI ecosystem with technologies like Agentic AI, LLMs, DeepSeek, Azure OpenAI, Google Gemini, Meta Llama and Microsoft Phi to drive innovation, create business opportunities and solve business problems.

Responsibilities

~2 min read

→Develop AI data architecture strategies, best practices, and standards for GenAI / AI usecases. Create data architecture strategies and roadmap for GenAI / AI platforms and technology stacks.
→Design and develop AI data architecture for GenAI / AI usecases including data ingestion, preprocessing, and scaled model computation, ensuring all SLAs are met with monitoring systems to track model performance and data quality.
→Troubleshoot complex issues related to machine learning model deployments and data pipelines, developing innovative solutions.
→Analyze business priorities & strategies and translate these into architecture requirements for the operational enterprise and propose to the business on strategic architecture framework development
→Provide Enterprise Data Architecture design thinking and support to the Enterprise Architecture team members, Technology Delivery IT and business team, with a focus on business and application architecture
→Contribute to the definition of data architecture strategy, direction, and standards pertinent for technology solution delivery. Ensure data architecture strategy aligns to the overall IT strategy and clearly communicated and understood among IT teams on delivery
→Be an active architecture team member and contribute to the architecture community on architecture roadmaps, blueprints and architecture building blocks development with domain leads
→Participate in Architecture assessment and reviews partnering with subject matter expert
→Ensure implementation and migration plan with risk management, business cost and benefit with intended values on work packages to be delivered
→Ensure ethical, secure, and compliant use of AI in line with industry standards, architecture standard and HK regulatory guidelines.

Requirements

~2 min read

Educated to degree level standard or above in information technology, computer science, engineering, or relevant field
10+ years in an data architect role ideally with insurance and/or health provider industry experiences with a desire to assume greater responsibilities as a leader and mentor, while remaining hands-on
4+ years of hands-on experience in AI Data architecture design and implementation for large-scale enterprise AI solutions
Experience in setting up Data Governance and processes in an enterprise environment
Experience with Cloud platforms (Azure preferred)
Experience with relational databases and data warehouse such as Azure SQL, SQL Server, Oracle or others
Experience with NoSQL DBs such as MongoDB, Azure Cosmos DB, ElastiCache, Redis, Neo4j or others
Experience with Big Data related solutions such as Azure Data Lake, Azure ML, Databrick, Azure Event Hub or others
Experience with statistical tools and building machine learning algorithms using tools such as Python, R or others
Experience with data visualization/analytic tools such as Tableau, MS Power BI or others
Experience influencing solution direction and standard adoption using architecture capability, building blocks, strategies and roadmaps
Experience work in complex IT environments, and able to prioritize and plan complex work in a rapidly changing context
Team player with experience leading and collaborating cross-team to ensure successful delivery of solutions
Experience with LLM integration, prompt engineering, and AI model governance. (E.g. RAG, AI data capture, Agentic AI, MCP protocol)
Familiarity with insurance-specific GenAI applications (e.g., policy summarization, chatbot assistants, fraud detection).

You are required to obtain the relevant license(s) if your job involves regulated activities

Build a career with us as we help our customers and the community live Healthier, Longer, Better Lives.

You must provide all requested information, including Personal Data, to be considered for this career opportunity. Failure to provide such information may influence the processing and outcome of your application. You are responsible for ensuring that the information you submit is accurate and up-to-date.