AI Infrastructure Engineer

AI Infrastructure Engineer

Location: Malaysia

Travel Requirement: Willingness to travel internationally as required

Language Requirements: English and other languages are an advantage

Core AI Engineering Competencies

AI Compute Cluster Deployment & Operations

• Hands-on experience in deploying, configuring, and operating GPU clusters ranging from hundreds to thousands of GPUs.

• Familiarity with NVIDIA GPUs and mainstream AI server hardware.

• Experience in GPU server installation, configuration, troubleshooting, and system optimisation.

High-Speed Networking & Storage

• Familiarity with 100G / 200G / 400G high-speed networking architectures, including InfiniBand (IB) and RoCE.

• Basic understanding of NVMe-based storage systems.

• Ability to perform basic network connectivity testing, troubleshooting, and fault isolation.

Linux & Cloud-Native Environment

• Strong proficiency in common Linux commands and system administration.

• Basic hands-on experience with Docker and Kubernetes.

• Ability to work with algorithm and AI engineering teams to build, configure, and maintain AI training environments.

Data Centre Infrastructure

• Understanding of data centre / IDC infrastructure, including:

• Rack planning and deployment

• UPS systems

• Power distribution

• Cooling infrastructure

• Liquid cooling and air cooling systems

Key Responsibilities

• Responsible for the installation, commissioning, deployment, go-live, and daily operations of AI compute centres, GPU servers, and supporting infrastructure.

• Participate in large-scale GPU cluster deployment, including network configuration, storage mounting, system environment deployment, and infrastructure troubleshooting.

• Assist in resolving basic hardware and software issues encountered during AI training workloads.

• Work closely with senior architects and technical leads on equipment selection, technical solution implementation, and on-site project deployment.

• Establish and maintain cluster monitoring, alerting, and operational procedures.

• Maintain operational logs and participate in incident reviews, root-cause analysis, and process optimisation.

• Coordinate with domestic and international suppliers, data centre operators, vendors, and engineering teams to ensure on-time project delivery and stable infrastructure operations.

Experience Requirements

• 3–5 years of experience in data centre operations, server hardware, networking, cloud computing, or related infrastructure operations.

• Experience in AI compute centres, GPU clusters, intelligent computing projects, or large-scale data centre projects is highly preferred.

• Experience with NVIDIA GPU infrastructure is an advantage.

Technical Background

• Degree or diploma in Computer Science, Information Technology, Computer Networking, Telecommunications, Electronic Engineering, or a related field.

• Strong foundation in Linux system administration and network troubleshooting.

• Good understanding of server hardware, networking, storage, and data centre infrastructure.

• Strong hands-on troubleshooting and problem-solving capabilities.

Execution & Responsibility

• Strong hands-on capability with the ability to independently undertake on-site implementation, commissioning, troubleshooting, and incident handling.

• Strong sense of ownership, responsibility, and execution.

• Ability to communicate and collaborate effectively across technical, engineering, vendor, and project teams.

Resilience & Adaptability

• Willingness to work in high-intensity project environments and respond to urgent infrastructure issues when required.

• Willingness to undertake frequent international travel for data centre and AI infrastructure projects.

• Strong interest in AI compute infrastructure and a commitment to continuously developing technical knowledge.

International Exposure & Career Opportunity

• Direct involvement in international AI compute centre and data centre projects.

• Opportunity to participate in the deployment and operation of large-scale GPU clusters, including projects ranging from hundreds to potentially 10,000+ GPUs.

• Gain hands-on experience across GPU infrastructure, high-speed networking, AI compute, data centre infrastructure, cloud platforms, and large-scale AI deployments.

• Build international project experience across Southeast Asia, the Middle East, and other global markets.