Data Solution Architect

About the Company

This role focuses on building enterprise data architecture for the AI era, responsible for the design and implementation of enterprise knowledge systems, semantic layers, ontology models, and AI data foundations.

This is not a traditional data warehouse, ETL, or BI platform role. Instead, it is a next-generation data architecture role centered around Ontology, Semantic Layer, Knowledge Graph, and AI Architecture. The core objective is to transform enterprise data from being storable and analyzable into data that is understandable, inferable, and consumable by AI Agents.

About the Role

Key Responsibilities

• Design enterprise-level AI data architecture, building AI-oriented data and knowledge foundations for Large Language Models (LLMs), AI Agents, knowledge bases, semantic search, and related AI applications.
• Plan and build core capabilities including domain ontology, business semantic layers, knowledge taxonomy, and knowledge graphs, establishing unified business concepts, entity relationships, metric semantics, and knowledge representation.
• Organize and govern structured, unstructured, and multimodal data through semantic modeling to improve readability, searchability, and reasoning capability for Large Language Models and AI Agents.
• Design AI-oriented data pipelines, including knowledge extraction, semantic modeling, vectorization, indexing, retrieval augmentation, context assembly, and tool invocation support.
• Collaborate with AI, product, business, and engineering teams to drive the implementation of AI use cases such as RAG, GraphRAG, ChatBI, Knowledge Q&A, and AI Workflow Agents.
• Build data governance and knowledge governance frameworks for AI scenarios, including semantic consistency, knowledge quality, data traceability, access control, security, and model usage governance.
• Continuously optimize data and knowledge architecture based on business scenarios to improve AI response quality, reasoning accuracy, generalization capability, and implementation efficiency.

Qualifications

• Bachelor's degree or above, preferably in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related disciplines.
• Minimum 5 years of experience in data, knowledge engineering, AI platforms, or architecture-related roles. Experience in ontology, semantic layer, knowledge graph, or AI data foundation development is preferred.
• Strong understanding of AI-era data architecture methodologies, going beyond traditional data warehouse modeling, with the ability to design enterprise data systems from the perspectives of knowledge organization, semantic representation, reasoning support, and AI Agent consumption.
• Familiarity with one or more of the following areas: Ontology, Semantic Modeling, Knowledge GraphRAG, Vector Database, LLM Application Architecture, Agentic AI.
• Ability to abstract business knowledge into domain models, conceptual systems, entity relationships, and semantic rules, transforming business language into AI-understandable knowledge structures.
• Experience working with both structured and unstructured data. Experience in text knowledge extraction, semantic retrieval, knowledge integration, or knowledge services is preferred.
• Strong architecture design and execution capabilities, with the ability to drive projects from solution design through PoC, implementation, and production deployment.
• Strong cross-functional communication skills, with the ability to collaborate effectively across business, product, AI, and engineering teams to deliver complex projects.
• Fluent English is required.

Preferred Skills

• Experience in knowledge modeling for complex industries such as Manufacturing, Healthcare, Automotive, or Financial Services.
• Experience delivering projects involving enterprise knowledge bases, intelligent question answering, AI management reporting, ChatBI, AI workflow agents, or multi-agent systems.
• Practical experience combining Knowledge Graphs with Large Language Models, or established methodologies in semantic layers, enterprise knowledge platforms, or AI governance.
• Familiarity with the OpenAI ecosystem, LangChain, LlamaIndex, Graph Databases, Vector Databases, and related technologies.
• Consulting and strategic planning capabilities, with the ability to design enterprise AI data architecture from both business strategy and business process perspectives.
• Cantonese as a working language is a plus.

You will play a key role in shaping next-generation enterprise AI capabilities, working at the intersection of Knowledge Architecture, Large Language Models, AI Agents, and Enterprise Transformation. This is an opportunity to help global enterprises build AI-native data foundations that enable intelligent automation, decision-making, and business innovation.

Equal Opportunity Statement

We are committed to diversity and inclusivity.