AI Engineer, Assistant Manager (Evergreen)

DKSH Management Ltd.; Kuala Lumpur; On-site; MYR 180,000 - 280,000; Full time

Job summary

DKSH is seeking an AI Engineer (MLOps) to design, deploy, and operate production-grade AI/ML solutions across the enterprise. You will work at the intersection of AI, software engineering, and cloud platforms to enable faster value from AI investments.

You will build scalable MLOps pipelines, automate CI/CD, and ensure performance, reliability, and cost efficiency across Azure environments. Strong Python, Databricks, MLFlow, and containerization skills are required.

Qualifications

• Bachelor's degree in CS, Engineering, or Data Science; cloud/AI engineering certs are a plus.
• Minimum 5 years in AI engineering, MLOps, DevOps, or software engineering with production AI experience.
• Strong hands-on MLOps and AI engineering experience.
• Proficiency in Python and software engineering best practices.
• Hands-on with Databricks and MLFlow for deployment and lifecycle management.
• CI/CD automation for AI/ML workloads.
• Experience with Microsoft Azure including Azure ML, Azure DevOps, and containers.
• Familiar with containerization and orchestration (Docker, Kubernetes).
• Exposure to generative AI and LLM deployment patterns.
• Experience in agile or product-focused delivery teams.
• Ability to build reliable, secure, scalable enterprise systems.

Responsibilities

• Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models.
• Engineer scalable deployment architectures across cloud environments, incl. Azure for batch and real-time inference.
• Implement automated workflows for model versioning, CI/CD, rollback, and lifecycle management.
• Ensure AI systems meet performance, reliability, security, and cost targets.
• Monitor data drift and performance; implement remediation for business continuity.
• Collaborate with AI Specialists, data scientists, and data engineers to productionize models.
• Develop reusable components and templates to accelerate AI delivery across markets.
• Integrate AI models into enterprise systems via APIs and services.
• Support generative AI and LLM deployments with guardrails and observability.

Skills

Python

Databricks

MLFlow

CI/CD

Azure ML

Kubernetes

Docker

Agile

Stakeholder comms

Education

Bachelor's degree in CS/Engineering/Data Science

Tools

Azure DevOps

Docker

Kubernetes

Job description

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Location: MY, MY

Global Business Unit: OTH

Job Function: Information Technology

Requisition Number: 247598

Description:

About the Role

The AI Engineer (Machine Learning Operations), Assistant Manager, Group Digital Transformation is an individual contributor role responsible for engineering, deploying, and operating production-grade Artificial Intelligence (AI) and Machine Learning (ML) solutions at scale across DKSH. This role sits at the intersection of AI, software engineering, and cloud platforms, enabling faster time-to-value from AI investments by establishing robust ML Operations (MLOps) practices and automation that power revenue-generating and mission-critical AI use cases globally.

What You Will Deliver

• Design, build, and maintain MLOps pipelines for training, testing, deploying, and monitoring AI/ML models in production, ensuring stable, reliable, and scalable performance.
• Engineer scalable model deployment architectures across cloud environments, including Microsoft Azure, to support both batch and real-time inference at enterprise scale.
• Implement automated workflows for model versioning, Continuous Integration and Continuous Deployment (CI/CD), rollback, and end-to-end lifecycle management.
• Ensure production AI systems consistently meet requirements for performance, reliability, security, and cost efficiency.
• Monitor models for data drift, performance degradation, and operational issues, and implement effective remediation strategies to sustain business continuity.
• Partner closely with AI Specialists, data scientists, and data engineers to successfully productionize models and analytics solutions.
• Develop reusable components, frameworks, and templates that accelerate AI delivery across markets and use cases.
• Integrate AI models into enterprise systems, digital products, and business workflows via Application Programming Interfaces (APIs) and services.
• Support the deployment of generative AI and Large Language Model (LLM)-based solutions with appropriate guardrails, observability, and operational controls.
• Define and enforce MLOps standards, best practices, and reference architectures to drive AI engineering maturity across DKSH.
• Contribute to documentation, runbooks, and knowledge sharing to uplift AI engineering capability across teams.
• Support audits, compliance, and responsible AI requirements from an engineering and operational perspective.
• Administrative duties and coordination tasks as required.

What You Bring

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field; relevant cloud, DevOps, or AI engineering certifications are an advantage.
• Minimum 5 years of experience in AI engineering, MLOps, DevOps, or software engineering roles, with demonstrated experience supporting production AI or data-driven systems at scale.
• Strong hands‑on experience in MLOps, AI engineering, or machine learning platform roles.
• Proficiency in Python and software engineering best practices.
• Hands‑on experience with Databricks and MLFlow for model deployment and lifecycle management.
• Practical experience with CI/CD pipelines and automation for AI/ML workloads.
• Experience with cloud platforms, preferably Microsoft Azure, including Azure Machine Learning (Azure ML), Azure DevOps, and container technologies.
• Strong understanding of the machine learning lifecycle, encompassing training, inference, monitoring, and retraining.
• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Familiarity with infrastructure-as-code and platform automation practices.
• Exposure to generative AI and Large Language Model (LLM) deployment patterns.
• Experience working in agile or product-oriented delivery teams.
• Ability to engineer reliable, secure, and scalable systems in complex enterprise environments.
• Strong problem‑solving mindset with close attention to operational detail.
• Ability to influence stakeholders and communicate effectively with both technical and non-technical audiences to drive cross‑functional collaboration.

Why Join DKSH

At DKSH, we help companies grow in Asia and enable people to perform at their best. You will be part of an organization that values accountability, collaboration, and long‑term partnerships. We offer a dynamic environment where your contributions are visible and where you can build a meaningful career in Digital Transformation. #LI-KP1