Job Ref ID: 1664969

刊登於 12-09-2026

月薪 Monthly

HKESE 提示聲明：我們無法確保招聘廣告的真偽。求職者在申請工作時應保持警覺，時刻小心提防招聘騙局，避免造成金錢或任何損失。常見求職陷阱、虛假招聘騙局 (守網者)。

a recognised university degree in computer science, artificial intelligence (AI), data science, engineering or related disciplines, with a minimum of 5 years’ post-qualification research experience in data and AI, engineering or related fields;
the ability to quickly acquire knowledge of the architecture, engineering and construction (AEC) domain;
hands-on experience in ontologies, graph databases, query languages (e.g., Cypher, SPARQL), schema design and semantic data modelling;
proven ability to develop agentic AI solutions and workflows using relevant frameworks and tools, such as LangChain, LlamaIndex, AutoGen, AG2 and Model Context Protocol, and to work with large language models, multi-agent systems and multimodal models;
proven hands-on experience in machine learning, transformer models, world models, natural language processing, computer vision and predictive analytics;
good research, analytical, problem-solving and technical documentation skills, with the ability to conduct experiments and proofs of concept, evaluate emerging technologies and translate research findings into practical and scalable solutions;
good interpersonal, communication, coordination and time management skills, with the ability to work independently and collaborate effectively with internal teams, external partners and vendors; and
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.)

to support the research and development of advanced agentic AI solutions for construction industry-related projects involving process automation and advanced analytics;
to build and scale knowledge graphs and develop other databases for information retrieval and AI-powered search;
to select and fine-tune appropriate machine learning, AI and large language model algorithms to optimise performance;
to collaborate with architecture, engineering and construction subject matter experts to integrate newly developed agentic AI solutions with building information modelling, geographic information systems and digital twin platforms;
to define evaluation metrics and validation plans for agentic AI systems;
to conduct experiments, proofs of concept and technical research on, and implement, emerging agentic AI, multi-agent systems and knowledge graph technologies;
to document research findings, model evaluation results, technical designs and implementation methodologies for internal knowledge sharing and future scaling;
to collaborate with internal teams, external partners and technology vendors to support project delivery and innovation initiatives;
to keep abreast of emerging technologies and industry trends, particularly in agentic AI, large language models, multimodal models, world models, knowledge graphs, building information modelling, geographic information systems and digital twin integration; and
to carry out any other duties as assigned by the Executive Director from time to time.