About the Client:Â 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.
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The Role & Landscape:Â 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.
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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.
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Why Apply To This Role:Â 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.
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If this outstanding opportunity sounds like your next career move, please submit through "Apply Now" or send your resume in Word format to Danny Kwan at resume@pinpointasia.com and put Engineering Manager (AI Platform & LLMOps) - Regional Hub - J13271 in the subject header.
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Data provided is for recruitment purposes only.
