AI Engineer - Industry Development

The applicant must possess:

1. a recognised university degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related fields;

2. a minimum of 5 years’ post-qualification work experience in Data Engineering, AI Engineering, or AI Product Development, with at least 1 year of hands-on experience in Knowledge Graphs;

3. professional certification as a Data or AI Engineer (Associate or Professional level) by AWS, Google Cloud, Microsoft Azure, or IBM will be an advantage;

4. proven experience in driving end-to-end AI product development, from gathering user requirements and rapid prototyping (MVP) to building production-grade services and managing iterative product rollouts;

5. solid background in data engineering, including designing and maintaining scalable ETL/ELT pipelines, data warehousing, handling unstructured AEC data (e.g., PDF drawings/specifications, spatial/point cloud data, IoT sensor streams), and working with vector databases (e.g., Qdrant, Chroma, pgvector);

6. solid hands-on experience in ontologies, graph databases, query languages (e.g., Cypher, SPARQL), schema/ontology design, and semantic data modelling to structure and retrieve engineering domain knowledge;

7. proven ability in LLM fine-tuning, agentic workflows (e.g., LangChain, LlamaIndex), multi-agent frameworks (e.g., AutoGen, AG2), and Model Context Protocol (MCP) tooling;

8. proficiency in ML/AI/Data platforms and infrastructure, including AWS (SageMaker, EC2), Azure AI, Databricks, Alibaba Cloud, and containerisation/orchestration technologies (Docker, Kubernetes);

9. hands-on experience in MLOps and LLMOps, including model serving (e.g., FastAPI, gRPC), token/latency/cost optimisation, guardrails, and automated evaluation frameworks;

10. proficiency in programming languages and database query technologies, including Python, .NET, C++, C#, SQL, and Cypher; knowledge of modern web stacks (JavaScript/TypeScript, React/Node.js) for AI product interfaces will be an advantage;

11. strong analytical, problem-solving, and technical documentation skills, with the ability to define benchmarking metrics, conduct rigorous validation, and translate technical discovery into scalable, reliable industry solutions;

12. good interpersonal, communication, stakeholder coordination, and time management skills, with the ability to work independently, collaborate effectively with multidisciplinary teams, and demonstrate high enthusiasm for innovation; and

13. good command of both written and spoken English and Chinese.

(Applicants who do not possess the required qualifications and experience may be considered for other positions within the organization.)

Duties include:

1. to lead the technical design, engineering implementation, and lifecycle delivery of advanced Agentic AI and data products for the construction sector, accelerating practical AI transformation for SMEs and industry stakeholders;

2. to design, build, and maintain robust data engineering pipelines, data lakes, and retrieval architectures capable of ingesting and processing structured, unstructured, and multimodal construction data (including BIM models, GIS spatial data, site inspection media, and IoT sensor streams);

3. to architect, scale, and maintain enterprise Knowledge Graphs and hybrid retrieval systems (integrating GraphRAG, vector databases, and semantic data models) for contextual AI search and intelligent reasoning;

4. to select, fine-tune, benchmark, and deploy appropriate machine learning, NLP, and large language model (LLM) algorithms to optimise performance, reliability, latency, and operational cost;

5. to collaborate with software engineers, AEC subject matter experts, and product stakeholders to integrate AI agents and services into BIM platforms, GIS systems, digital twin environments, and web/mobile client applications;

6. to establish comprehensive evaluation benchmarks, LLMOps pipelines, guardrails, and automated testing harnesses to ensure product robustness, safety, and compliance with data governance standards;

7. to develop, deploy, and maintain scalable containerised microservices and cloud infrastructure across platforms such as AWS, Azure, Databricks, and Alibaba Cloud;

8. to explore frontier AI technologies, conducting rapid feasibility studies and proof-of-concept (PoC) builds to evaluate emerging agentic frameworks and MCP integrations for industry adoption;

9. to produce clear technical documentation, API specifications, system architecture designs, and user guidelines to facilitate smooth knowledge transfer, maintainability, and product scaling;

10. to collaborate with internal departments, external industry partners, academic institutions, and technology vendors to ensure project delivery and drive technology adoption across the local construction ecosystem; and

11. to carry out any other duties as assigned by the Executive Director from time to time.

Applications:

The position is on a renewable fixed-term contract (subject to performance and operational needs) for a period of 2 years.

Please click the below “Apply Online” to complete the application form and upload the updated curriculum vitae, the results of English and Chinese Language obtained in public examinations, current and expected salary together with a covering letter stating one’s suitability for the job on or before 22 October 2026.

For further details on CIC please refer to website: http://www.cic.hk.