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 (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