AI Infrastructure Engineer

TOSS-EX PTE. LTD.; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

A technology solutions provider in Singapore is looking for an AI Infrastructure Engineer to design and maintain high-performance AI computing environments. The role involves pre-sales technical support, onsite installations, and troubleshooting of AI infrastructure. Candidates should possess a Bachelor's degree in Computer Science and over 5 years of experience with server OEM environments, specifically with NVIDIA AI infrastructure. Strong problem-solving and customer service skills are essential for this role.

Qualifications

• 5+ years of experience in server OEM environments or AI computing.
• Strong understanding of CPU/GPU architectures.
• Hands-on experience with NVIDIA AI infrastructure.

Responsibilities

• Provide pre-sales technical support for AI solutions.
• Perform onsite installation of AI infrastructure.
• Diagnose and troubleshoot hardware and software issues.

Skills

Technical Consultation

Installation and Configuration

Troubleshooting

Customer Engagement

Problem-Solving

Education

Bachelor’s degree in Computer Science or related field

Tools

NVIDIA GPU systems

Linux

Job description

Job Summary

As a key member of the AI Services Division, the AI Infrastructure Engineer will be responsible for designing, deploying, and maintaining high-performance AI computing environments. The role focuses on NVIDIA GPU-based systems and requires deep technical expertise in AI infrastructure and server technologies. The ideal candidate will combine strong technical acumen with hands‑on experience in system implementation and customer engagement.

Responsibilities

• Pre‑Sales Technical Support – Provide pre‑sales technical consultation for AI servers and related hardware solutions, including requirements analysis, solution design, performance evaluation, and technical communication. Understand customers’ AI application scenarios (e.g., large‑model training, inference, HPC computing, and data analytics) to recommend optimal server configurations and system architectures. Collaborate with the sales team to prepare technical proposals, bidding documentation, solution presentations, and demonstrations. Participate in Proof of Concept (POC) testing, performance tuning, and solution validation to ensure alignment with customer business objectives.
• Deployment Support
  • Physical Deployment – Perform onsite installation of AI infrastructure, including server setup, network integration, cabling, and labeling.
  • Logical Configuration – Configure systems and networks, conduct validation tests, and benchmark performance.
  • Operational Enablement – Deliver system configuration and operation documentation. Implement foundational operational tools (e.g., monitoring and alerting systems).
• Maintenance and Support – Diagnose and troubleshoot hardware and software issues in AI infrastructure. Perform hardware replacement, software updates, or implement workarounds as required. Escalate complex technical issues to vendors for advanced support when necessary.

Qualifications and Skills

Bachelor’s degree or higher in Computer Science, Electronics, Communications, Information Engineering, or a related discipline.

5+ years of experience in server OEM environments or related fields such as AI computing, big data, or HPC infrastructure.

Strong understanding of server hardware architectures (CPU/GPU, memory, storage, networking).

Hands‑on experience deploying or maintaining large-scale NVIDIA AI infrastructure, including at least one of the following: B200, GB200, or GB300.

Familiarity with major computing platforms such as NVIDIA, Intel, and AMD.

Excellent problem‑solving, collaboration, and customer service skills.

Proficient in English (reading and writing); able to interpret technical documentation and communicate effectively.

Preferred Attributes

Experience working with AI infrastructure deployment at scale in enterprise or data‑center environments.

Knowledge of Linux system administration, performance tuning, and monitoring tools.

Strong analytical mindset and eagerness to learn emerging AI technologies.