Lead GenAI & Data Architect (Asia CoE)

Randstad Hong Kong Limited; Hong Kong; On-site; HKD 900,000 - 1,400,000; Full time

Job summary

Randstad Hong Kong Limited seeks a Senior AI & Data Architect to lead enterprise-scale GenAI innovation across Asia from Hong Kong. You will build scalable data ecosystems, deploy Agentic AI, and ensure HKMA-compliant AI frameworks within a centralized CoE.

You will guide architecture across data ingestion, feature stores, real-time preprocessing, and large-scale model orchestration, while enforcing governance, security, and cross-functional collaboration with IT Delivery teams.

Qualifications

• Bachelor’s degree or above in a technical discipline.
• 10+ years of professional data architecture experience with leadership.
• 4+ years deploying enterprise AI/ML and GenAI infra.
• Hands-on exposure to LLM stack, RAG, Agentic AI, prompts, and model governance.

Responsibilities

• Establish roadmaps, blueprints, and governance for enterprise AI/ML stacks.
• Lead end-to-end architecture for data ingestion, feature stores, real-time preprocessing, and large-scale model orchestration.
• Translate business goals into architecture specs aligning with Enterprise Architecture and IT Delivery.
• Resolve bottlenecks in ML deployments, pipelines, and cloud integrations.
• Enforce ethical AI, data security, and HKMA/IA regulatory compliance across AI workflows.

Skills

Data architecture leadership

Enterprise AI/ML

GenAI infrastructure

LLM stack experience

Azure cloud

Data lakes

Python/R for ML

Cross-functional influence

Education

Bachelor’s degree in Computer Science/Software/Data Engineering

Tools

Azure

Databricks

NoSQL databases

Relational databases (Azure SQL, Oracle)

Job description

Randstad Hong Kong Limited seeks a Senior AI & Data Architect to lead enterprise-scale GenAI innovation across Asia from Hong Kong. You will build scalable data ecosystems, deploy Agentic AI, and ensure HKMA-compliant AI frameworks within a centralized CoE.

You will guide architecture across data ingestion, feature stores, real-time preprocessing, and large-scale model orchestration, while enforcing governance, security, and cross-functional collaboration with IT Delivery teams.