Engineering Manager (AI Platform & LLMOps) - Regional Hub - J13271

Pinpoint Asia; Hong Kong; On-site; HKD 700,000 - 1,300,000; Full time

Job summary

Pinpoint Asia represents a large enterprise seeking an Engineering Manager for AI Platform & LLMOps in Hong Kong. You will lead a geographically distributed ML engineering team, partner with Data Science to deploy, monitor, and scale GenAI models in production, and own the end-to-end delivery pipeline.

The role prioritizes establishing standard deployment workflows, CI/CD, and robust LLMOps, while acting as the technical authority for GenAI architectures and collaborating with PMs, IT, and

Qualifications

• Two years of formal people management experience (performance reviews, hiring, coaching).
• Practical experience taking ML/Generative AI applications into production.
• Strong command of modern infrastructure and deployment tooling (MLOps, LLMOps, CI/CD, containerization).

Responsibilities

• Lead and scale a geographically distributed ML engineering team.
• Own end-to-end delivery pipelines for production ML/GenAI deployments.
• Establish standardized deployment workflows with robust CI/CD and LLMOps practices.
• Act as the technical authority for GenAI deployment architectures.

Skills

People management

ML in production

LLMOps

CI/CD

Containerization

Kubernetes

Tools

Azure

Databricks

Kubernetes

Job description

Engineering Manager (AI Platform & LLMOps) - Regional Hub - J13271

About the Client: We are representing a highly established, large-scale enterprise with a dedicated AI/Data Lab. They are moving beyond proof-of-concept AI and are aggressively embedding Machine Learning, Generative AI, and Agentic AI into their core business operations. They operate a complex, shared IT infrastructure and require robust engineering governance to scale their AI capabilities efficiently across multiple business units.

The Role & Landscape: This is not a model-building role. You will partner with the Data Science team to take their models and orchestrate the engineering required to deploy, monitor, and scale them in production.

Manage, coach, and scale a geographically distributed team of Machine Learning Engineers.

Own the end-to-end MLE delivery pipeline, ensuring solutions are secure, scalable, and maintainable.

Drive "Engineering Transformation" by establishing standardized deployment workflows, reusable components, and robust CI/CD and LLMOps practices.

Act as the technical authority for deployment architectures involving GenAI and Agentic AI.

Navigate complex cross-functional dependencies, working daily with Programme Managers, IT, Data Engineering, and external vendors.

What We Are Looking For:

A seasoned Software or ML Engineer with at least 2 years of formal people management experience (conducting performance reviews, hiring, coaching).

Deep practical experience taking Machine Learning and Generative AI applications into production.

Strong command of modern infrastructure and deployment tooling (MLOps, LLMOps, CI/CD, Containerization).

Familiarity with cloud ecosystems (Azure/Databricks preferred) and Kubernetes.

The maturity to establish engineering standards without becoming a bottleneck, balancing speed-to-market with production reliability.

Why Apply To This Role: You are joining at a critical inflection point. The business has proven the value of AI; your mandate is to build the engine that scales it. This offers immense autonomy to define engineering standards, adopt GenAI-assisted development tools, and build out a regional team within a highly stable, resource-rich enterprise environment.