Head of Data / AI

Quam Plus International Financial Limited; Hong Kong; On-site; HKD 2,000,000 - 4,000,000; Full time

Job summary

Quam Plus International Financial Limited is seeking a hands-on technical leader to architect and deliver scalable AI platforms in a regulated financial services environment. You will lead a team to translate business needs into production AI solutions that create measurable value.

You will drive MLOps/LLMOps, design multi‑agent architectures, and ensure secure, compliant deployment while collaborating with business stakeholders to deliver tangible outcomes.

Qualifications

• Bachelor or Master degree in Computer Science, Data Engineering, or a related discipline.
• 5+ years of software engineering experience with at least 2 years focused on building and scaling AI/ML platforms and infrastructure.
• Strong hands-on expertise in LLMs, generative AI, RAG pipelines, and agentic systems.
• Proven experience with MLOps/LLMOps, containerisation (Docker), orchestration (Kubernetes), and Infrastructure‑as‑Code.
• Proficiency in Python and modern AI frameworks (PyTorch, Hugging Face, etc.).
• Experience in financial services or regulated industries.
• Excellent communication skills and fluency in English and Chinese.

Responsibilities

• Lead design, development, and scaling of robust AI/ML platforms and infrastructure (on‑premises and hybrid).
• Drive MLOps, LLMOps, and AgentOps to accelerate model development, deployment, and lifecycle management.
• Deploy, optimise, and scale LLM and agent workflows with focus on performance and observability.
• Develop and maintain robust ETL/ELT pipelines from multiple data sources.
• Architect a modern data warehouse / Lakehouse with modelling standards and performance optimization.
• Collaborate with AI and business teams to deliver clean, feature‑ready data for models and use cases.
• Fine‑tune models, design evaluation/monitoring, and implement multi‑agent architectures with guardrails.
• Evaluate emerging technologies and implement IaC (Kubernetes, etc.).
• Build and mentor a high‑performing AI solution team; champion AI‑assisted development.

Skills

AI strategy

MLOps

LLMOps

Kubernetes

Docker

Python

Data engineering

Solution architecture

Stakeholder collaboration

Education

Bachelor’s or Master’s in CS/Data Eng

Tools

Docker

Kubernetes

ETL/ELT tooling

Hugging Face/ PyTorch

Job description

We are seeking a hands‑on technical leader to drive our AI strategy and build enterprise‑grade AI capabilities from the ground up. You will architect and deliver scalable AI platforms, lead a talented team, and translate business needs into production AI solutions that create measurable value.

This is a leadership position for a technical expert who combines deep AI expertise with a strong delivery focus and the ability to operate effectively in a regulated environment.

Responsibilities

Lead the design, development, and scaling of robust AI/ML platforms and infrastructure (on‑premises and hybrid).

Drive MLOps, LLMOps, and AgentOps practices to accelerate model development, deployment, and lifecycle management.

Deploy, optimise, and scale Large Language Model (LLM) and agent workflows with a focus on performance, cost, reliability, and observability.

Develop, optimise, and maintain robust ETL/ELT pipelines for data ingestion, transformation, and loading from internal systems, external feeds, and market data sources.

Architect and implement a modern data warehouse / Lakehouse, including data modelling standards, dimensional modelling, and performance optimisation.

Collaborate with AI and business teams to deliver clean, feature‑ready data for models, RAG systems, and decision‑making use cases.

Fine‑tune models, design robust evaluation and monitoring systems, and implement multi‑agent architectures with appropriate guardrails.

Evaluate emerging technologies, lead proof‑of‑concept initiatives, and implement Infrastructure‑as‑Code (Kubernetes, etc.).

Team Leadership & Business Alignment

Build, mentor, and lead a high‑performing AI solution team.

Champion the adoption of AI‑assisted development practices across the organisation.

Serve as the key bridge between business stakeholders and technical teams, translating requirements into deliverable AI initiatives.

Actively contribute hands‑on through architecture reviews, solution design, and critical implementation work.

Infrastructure, Operations & Governance

Ensure high availability, performance, and cost‑efficiency of AI infrastructure.

Maintain secure, compliant, and repeatable deployment processes in line with regulatory standards.

Manage operational excellence, incident response, and continuous improvement of AI platforms.

Requirements

Bachelor or Master degree in Computer Science, Data Engineering, or a related discipline.

5+ years of software engineering experience with at least 2 years focused on building and scaling AI/ML platforms and infrastructure.

Strong recent hands‑on expertise in LLMs, generative AI, RAG pipelines, and agentic systems.

Proven experience with MLOps/LLMOps practices, containerisation (Docker), orchestration (Kubernetes), and Infrastructure‑as‑Code.

Proficiency in Python and modern AI frameworks (PyTorch, Hugging Face, etc.).

Experience working in financial services or other regulated industries.

Excellent communication skills and fluency in both English and Chinese (written and spoken).

This role offers the opportunity to shape the future of AI within a dynamic financial services organisation and deliver solutions that drive real business impact.