AI Engineering Lead (GenAI / Platform)

Michael Page International (Hong Kong) Limited; Hong Kong; On-site; HKD 900,000 - 1,200,000; Full time

Job summary

Michael Page International (Hong Kong) Limited is seeking an experienced AI Platform Lead to spearhead a flagship AI transformation programme within a leading financial institution. This role entails building and scaling an enterprise AI platform supporting advanced AI use cases like Generative AI.

The ideal candidate will lead a team of engineers and collaborate across business and technology teams while driving MLOps and AI infrastructure initiatives. Strong communication skills and experience within financial services are essential.

Qualifications

• Proven experience in AI/ML platform engineering or AI infrastructure development.
• Strong understanding of modern AI concepts such as GenAI, RAG pipelines, and LLM frameworks.
• Experience with MLOps / LLMOps practices and AI deployment lifecycle.

Responsibilities

• Lead a team of engineers in designing and building scalable AI / ML platforms.
• Drive adoption of MLOps, LLMOps, and AI operational frameworks.
• Design and implement AI infrastructure with a focus on performance and scalability.

Skills

AI/ML platform engineering

MLOps

Containerization (Docker, Kubernetes)

Programming (Python, SQL, Bash)

Communication skills

Education

Degree in Computer Science, Engineering, or related discipline

Tools

GPU-based environments

AI platforms (MLFlow, Jupyter)

Job description

• Be part of a flagship AI transformation programme
• High visibility role working across business and technology teams

About Our Client

We are partnering with a leading financial institution in Hong Kong that is undergoing a large-scale digital transformation, with strong investment in AI, data, and innovation capabilities. As part of this journey, they are expanding their AI engineering team and looking for an experienced AI Platform Lead to drive the development of next-generation AI infrastructure.

This is an exciting opportunity to play a key role in building and scaling an enterprise AI platform from the ground up, supporting advanced AI use cases including Generative AI and knowledge-based systems.

Job Description

• Lead a team of engineers in designing and building scalable AI / ML platforms
• Drive adoption of MLOps, LLMOps, and AI operational frameworks to improve model lifecycle management
• Design and implement AI infrastructure (on-prem / hybrid) with strong focus on performance and scalability
• Partner with data scientists and AI engineers to support model development, deployment, and optimisation (e.g. RAG-based solutions)
• Develop and manage Infrastructure-as-Code (Terraform, Kubernetes, etc.)
• Evaluate new AI technologies and lead proof-of-concept initiatives
• Act as a key interface between business stakeholders and technical teams, managing expectations, priorities, and delivery scope
• Perform hands‑on technical work, including design reviews, coding, and solution validation

The Successful Applicant

• Degree in Computer Science, Engineering, or related discipline
• Proven experience in AI/ML platform engineering or AI infrastructure development
• Strong understanding of modern AI concepts such as GenAI, RAG pipelines, LLM frameworks
• Experience with MLOps / LLMOps practices and AI deployment lifecycle
• Hands‑on experience with containerisation and orchestration (Docker, Kubernetes)
• Strong programming/scripting skills (e.g. Python, SQL, Bash)
• Experience working with GPU‑based environments and high‑performance AI workloads
• Familiarity with DevOps / DevSecOps tools (CI/CD, Git, automation frameworks)
• Strong communication skills with the ability to work across technical and non‑technical stakeholders
• Experience within financial services / regulated environments
• Exposure to AI platforms and tooling (MLFlow, Jupyter, vector databases, etc.)
• Knowledge of data security, governance, and AI risk considerations

What's on Offer

• Be part of a flagship AI transformation programme
• Opportunity to build an enterprise AI platform from scratch
• High visibility role working across business and technology teams
• Mix of leadership + hands‑on architecture / engineering
• Exposure to cutting‑edge AI technologies (GenAI, LLMs, knowledge platforms)