AI Infrastructure Architect – GPU Compute & Networking

Gateway Search; Singapore; Presencial; SGD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Gateway Search Pte Ltd is seeking an AI Infrastructure Architect in Singapore to design and deliver GPU infrastructure, including servers, networking, and rack deployment. You will validate hardware, plan connectivity, and support deployment with vendors and data center teams.

The role requires hands-on experience with GPU server architectures and high-speed networking like InfiniBand or RoCE. You will work closely with vendors and engineers to ensure robust, scalable solutions.

Formación

• Hands-on experience designing GPU infrastructures and data center deployments.
• Experience selecting GPU servers, CPUs, memory, NICs, and storage for performance and cost.
• Ability to design cluster topology and connectivity plans, including switches and uplinks.

Responsabilidades

• Design GPU infrastructure solutions for compute servers, networking, storage, and rack deployment.
• Evaluate GPU servers and components balancing performance, availability, and cost.
• Develop cluster network topology, switch sizing, uplinks, and cabling plans.
• Produce architecture proposals and BOMs with vendors for validation and feasibility.
• Provide guidance during installation, bring-up, and testing; troubleshoot hardware issues.
• Coordinate with data center teams on rack space, power, and cooling requirements.
• Demonstrate strong communication and technical documentation skills.

Conocimientos

GPU infrastructure

Cluster networking

Vendor coordination

Technical documentation

Power/cooling planning

Educación

Bachelor's degree in Computer Science or related

Herramientas

InfiniBand

RoCE

NVLink

NVSwitch

Descripción del empleo

We are looking for an AI Infrastructure Architect to design and deliver GPU infrastructure, with a focus on server hardware, high-speed networking, and physical connectivity.

This is a hands-on technical individual contributor role covering infrastructure design, hardware selection, solution validation, and deployment support. You will work with equipment vendors, network engineers, and data center delivery teams to translate capacity and performance requirements into practical infrastructure solutions.

Key Responsibilities

• Design GPU infrastructure solutions covering compute servers, cluster networking, storage connectivity, and rack-level deployment.
• Evaluate and select GPU servers and supporting components, including CPUs, memory, NICs, and storage, balancing performance, compatibility, availability, and cost.
• Develop cluster network topology and connectivity plans, including switch sizing, port allocation, uplinks, and optical transceiver or cable selection.
• Produce architecture proposals and bills of materials (BOMs), working with vendors to validate component compatibility and solution feasibility.
• Provide technical guidance during installation, bring-up, and acceptance testing, and help resolve hardware or connectivity issues.
• Coordinate with data center facilities teams on rack space, power, and cooling requirements.
• At least 5 years of relevant experience in server infrastructure, HPC/AI infrastructure, data center networking, or infrastructure solution architecture.
• Practical experience designing or deploying GPU infrastructure, with clear personal responsibility for hardware selection, network design, or technical validation.
• Solid understanding of GPU server architecture and component compatibility, including PCIe, GPU interconnects, and network interfaces.
• Hands-on experience with at least one high-speed cluster networking technology: InfiniBand or RoCE, including switch connectivity and topology planning.
• Practical knowledge of optical transceivers, fiber, DAC, and AOC selection, including compatibility, distance, and deployment considerations.
• Ability to develop technical proposals and BOMs, evaluate vendor solutions, and support deployment and troubleshooting.
• Strong communication, vendor coordination, and technical documentation skills.

Preferred Experience

• Experience with NVIDIA HGX or comparable multi-GPU platforms, including NVLink/NVSwitch-based systems.
• Experience with multi-rack GPU clusters or AI/HPC deployments at scale.
• Exposure to high-density racks, liquid cooling, or infrastructure performance testing.
• Bachelor's degree in Computer Science, Engineering, Communications, or a related discipline, or equivalent practical experience.