Network Architect (GPU AI Data Centres)

Experis UK; Belfast City District; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

On-site facilities

Job summary

Experis UK is seeking an AI GPU Network Infrastructure Architect in Belfast (hybrid) to lead architecture for large-scale NVIDIA GPU deployments.

You will define power, cooling, networking, rack density and cluster standards while coordinating with data centre and NVIDIA ecosystem partners to enable AI training and inference at scale.

Qualifications

• Experience with NVIDIA AI platforms (DGX/HGX) is required.
• Strong knowledge of AI training and inference architectures.
• Deep understanding of GPU networking technologies.
• Experience with data centre power and cooling constraints.
• Ability to communicate with technical and executive stakeholders.

Responsibilities

• Define and validate architecture for large-scale NVIDIA GPU deployments.
• Develop AI cluster design standards for training and inference workloads.
• Collaborate with data centre design teams to align compute needs.
• Define rack density, power, and cooling strategies for high-density AI environments.
• Provide technical leadership around NVIDIA DGX, HGX, Blackwell and future GPUs.
• Design GPU networking and fabric requirements (NVLink, NVSwitch, InfiniBand).
• Support capacity planning and scaling for 20-30MW AI compute estate.
• Evaluate liquid cooling and advanced thermal management solutions.
• Coordinate with infrastructure, cloud, networking and operations teams.
• Engage with vendors and systems integrators; produce architecture roadmaps.
• Provide technical oversight during deployment and commissioning phases.

Skills

Stakeholder communication

AI compute architecture

Data centre design

Thermal management

Project leadership

Tools

NVIDIA DGX

NVIDIA HGX

InfiniBand

NVLink

NVSwitch

High-speed Ethernet

Liquid cooling

Job description

Contract - AI GPU Network Infrastructure Architect

Location: Belfast (Hybrid)

Start: ASAP

We are supporting the transformation of an existing data centre campus into a next-generation AI-ready facility capable of supporting large-scale NVIDIA GPU deployments, AI training clusters, HPC workloads, and high-density compute environments.

This is a unique opportunity to help shape the design and implementation of one of the UK's emerging AI infrastructure platforms, working alongside data centre, electrical, mechanical, network, and NVIDIA ecosystem specialists.

As the AI GPU Infrastructure Architect, you will lead the technical architecture and deployment strategy for large-scale GPU compute environments, ensuring the facility is capable of supporting current and future generations of NVIDIA AI infrastructure.

You will act as the bridge between AI compute requirements and data centre design, helping define power, cooling, networking, rack density, and cluster architecture standards.

Key Responsibilities

• Define and validate architecture for large-scale NVIDIA GPU deployments
• Develop AI cluster design standards supporting training and inference workloads
• Work with data centre design teams to align compute requirements with facility capabilities
• Define rack density, power, and cooling strategies for high-density AI environments
• Provide technical leadership around NVIDIA DGX, HGX, Blackwell and future GPU platforms
• Design GPU networking and fabric requirements including NVLink, NVSwitch and InfiniBand
• Support capacity planning and scaling strategies for a 20-30MW AI compute estate
• Evaluate liquid cooling and advanced thermal management solutions
• Collaborate with infrastructure, cloud, networking and operations teams
• Engage with vendors including NVIDIA, OEM partners and systems integrators
• Produce architecture documentation, standards and implementation roadmaps
• Provide technical oversight during deployment and commissioning phases

Required Experience

• Experience with NVIDIA AI platforms including DGX and/or HGX systems
• Strong understanding of AI training and inference architectures
• Deep knowledge of GPU networking technologies

Experience with:

• NVLink
• NVSwitch
• InfiniBand
• High-speed Ethernet
• Strong understanding of data centre power and cooling constraints
• Experience supporting high-density rack deployments
• Ability to communicate with both technical and executive stakeholders
• Blackwell, Hopper or Grace-Blackwell platforms
• AI Factory or sovereign AI programmes
• Data centre design and commissioning
• Colocation or hyperscale environments
• MLOps and AI platform architecture
• Validate facility readiness for AI workloads
• Establish rack density and power standards
• Define cooling and thermal requirements
• Create phased scaling plans from initial deployment through full 20-30MW operation
• Support procurement and vendor selection activities
• Provide technical assurance throughout implementation