AI Infrastructure Engineer

Salary: ฿50,000 – ฿70,000 per month

About the role

The AI Infrastructure Engineer is responsible for the installation, commissioning, deployment, go-live, and daily operations of AI compute centres, GPU servers, and supporting infrastructure. You will participate in large-scale GPU cluster deployment, including network configuration, storage mounting, system environment deployment, and infrastructure troubleshooting. You will work closely with senior architects and technical leads on equipment selection, technical solution implementation, and on-site project deployment.

Key responsibilities

• Install, commission, deploy, and manage 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

About you

• 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

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

• 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

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

• Strong proficiency in common Linux commands and system administration

• Basic hands-on experience with Docker and Kubernetes

• Strong hands-on troubleshooting and problem-solving capabilities