Assistant Manager, Information Technology (AI Application Development)

Urban Renewal Authority 市區重建局; Hong Kong; On-site; HKD 600,000 - 960,000; Full time

Job summary

Urban Renewal Authority 市區重建局 in Hong Kong is seeking an experienced AI/ML engineer to design, prototype, and deploy end-to-end AI/ML solutions across business and IT teams. You will build generative AI applications, establish RAG patterns, and implement LLMOps for safe production deployment.

The role requires hands-on AI/ML development with 5+ years of IT experience, proficiency in Python and major frameworks, and strong bilingual communication in English and Chinese.

Qualifications

• Bachelor’s degree in CS/AI/related quantitative field.
• Hands-on AI/ML development with prototyping and deployment.
• Proficient in Python and major AI frameworks.
• Experience with LLM solutions, RAG, prompt engineering, and LLMOps.
• Understanding of security, privacy, and compliance for AI.
• Strong analytical, problem-solving, and delivery skills.
• Excellent written and spoken English and Chinese.

Responsibilities

• Collaborate with business and IT teams to understand workflows and requirements.
• Prototype, validate, and build AI, machine-learning, and automation solutions.
• Assist in scoping integrations with existing applications, databases, APIs, identity services, and infrastructure, identifying risks and dependencies early.
• Define measurable acceptance criteria, evaluation datasets, rollout approaches, and support arrangements in collaboration with project stakeholders.
• Design, develop, and implement end-to-end AI/ML solutions, including predictive models, NLP, computer vision, decision support, automation, and generative AI applications.
• Build and integrate robust generative AI patterns (RAG, fine-tuning, prompt engineering) with LLMOps for evaluation, monitoring, and safe deployment.
• Prepare and process data for AI solutions, including feature engineering, labeling, embeddings, vectorization, and data-quality checks.
• Support deployment through pilots and production rollouts; troubleshoot incidents.
• Monitor quality, latency, cost, security, adoption, and business outcomes.
• Implement AI strategy, policies, standards, and technical controls (security, privacy, access-control, Responsible AI).
• Evaluate emerging AI technologies, including foundation and multimodal models, agentic workflows, vector databases, and orchestration frameworks.

Skills

Python

AI/ML frameworks

NLP

LLMOps

Prototyping

Data analysis

Communication

Education

Bachelor’s degree in Computer Science

Data Science

AI-related field

Statistics

Engineering

Tools

scikit-learn

PyTorch

TensorFlow

Hugging Face Transformers

LangChain

LlamaIndex

Job description

• Collaborate with business and IT teams to understand workflows and requirements.
• Prototype, validate, and build AI, machine-learning, and automation solutions.
• Assist in scoping integrations with existing applications, databases, APIs, identity services, and infrastructure, identifying risks and dependencies early.
• Define measurable acceptance criteria, evaluation datasets, rollout approaches, and support arrangements in collaboration with project stakeholders.
• Design, develop, and implement end-to-end AI/ML solutions, including predictive models, NLP, computer vision, decision support, automation, and generative AI applications.
• Build and integrate robust generative AI patterns (such as retrieval-augmented generation (RAG), fine-tuning, prompt engineering, and guardrails) and implement LLMOps practices for model evaluation, monitoring, and safe deployment.
• Prepare and process data for AI solutions, including feature engineering, labeling, embeddings, vectorization, and data-quality checks, to build reliable and maintainable production components.
• Support the deployment of solutions through controlled pilots and production rollouts and troubleshoot incidents.
• Monitor quality, latency, cost, security, adoption, and business outcomes.
• Implement AI strategy, policies, standards, and technical controls (including security, privacy, access-control, and Responsible AI practices) within assigned solutions.
• Assist in evaluating and experimenting with emerging AI technologies, including foundation and multimodal models, agentic workflows, vector databases, and orchestration frameworks to build focused proofs of concept.

Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related quantitative field.
• Hands-on experience in AI/ML, data science, or generative AI development (including prototyping, building, integration, or deployment), with around 5 years of relevant IT experience.
• Proficiency with Python and common AI/ML frameworks and tools (e.g., scikit-learn, PyTorch/TensorFlow, Hugging Face Transformers, LangChain/LlamaIndex).
• Experience in designing and implementing LLM solutions, including RAG pipelines, prompt engineering, fine-tuning, and LLMOps, with an understanding of cloud-based, on-premises, or hybrid deployments.
• Good understanding of security, privacy, and compliance requirements for AI (PII handling, access controls, encryption, secrets management, prompt-injection defenses).
• Strong analytical, systems-thinking, troubleshooting, and delivery skills, with a track record of delivering production-ready AI or data solutions.
• Excellent communication and interpersonal skills, with the ability to explain complex technical concepts clearly in both English and Chinese to diverse stakeholders at all levels.
• Proactive, innovative, security-conscious, and comfortable working independently in a dynamic, rapidly changing technical environment.
• Excellent command of written and spoken English and Chinese.

Closing date for application

24 September 2026

For more information on the work of the URA, please visit the website at http://www.ura.org.hk.

All applications will be treated in the strictest confidence and information provided will be used for the consideration of applications. Applicants not invited for interview within four weeks from the closing date may consider their applications unsuccessful.

Personal data provided by job applicants will be treated in strict confidence and used strictly in accordance with our “Personal Information Collection Statement Pertaining to Recruitment” for recruitment purpose only. A copy of the Statement is available on our website and obtainable on request. Applicants may be considered for other suitable positions in the Authority and all personal data of unsuccessful applicants will be retained for a maximum of two years.