Infrastructure Deployment Engineer (AI Factory Delivery)

**🗓️ Full-time Permanent**

📍 Remote, in the same time zone as the rest of the squad

🏡 Remote working

About Sharon AI

Sharon AI is an Australian neocloud, delivering trusted AI infrastructure organisations need to build, train and run AI at scale. We support customers across the full AI lifecycle, from training through to inference and agentic AI, drawing on a strong ecosystem of technology and co-location partners to deliver capability where it’s needed. As the first neocloud to join NVIDIA’s AI Compute Program, we’re growing quickly, scaling our AI Factory platform to meet rising demand for advanced compute.

The Role

As Sharon AI continues to grow, we’re looking for a talented Infrastructure Deployment Engineer to join our regional Delivery squad and play an important role in deploying and delivering the infrastructure layer of our AI Factories, reporting to our Regional Delivery Manager.

AI Factories are the high-performance GPU compute environments that underpin Sharon AI’s AI cloud, serving customers and internal teams running large-scale training, fine-tuning and inference. In this role, the Infrastructure Deployment Engineer will take the GPU nodes and underlying cluster infrastructure of each AI Factory from hardware staging through to customer acceptance, and build and run the automation that deploys and tests them. You’ll deploy, test and automate, and look for ways to make each deployment faster than the last, with reducing deployment time a core part of the job. You’ll work closely with Network and Platform Deployment Engineers, on-site Data Centre Deployment Engineers, the Infrastructure and Platform teams and Operations, with exposure to cutting-edge technology at the forefront of AI infrastructure.

What You’ll Be Doing

• Deploying and configuring the underlying cluster infrastructure (Kubernetes and/or HPC schedulers such as Slurm) with the Platform Deployment Engineers, from initial build through to handover
• Provisioning and configuring GPU nodes: operating system images, firmware and drivers at the locked versions, to meet agreed design and performance targets
• Configuring server management controllers (BMC) to the standard settings using Redfish or IPMI, and validating PCIe, NVLink and GPUDirect configuration on every node
• Connecting VAST Data storage, deploying monitoring, logging and alerting agents, and applying node-level security controls and workload isolation
• Working with on-site staff and the data centre provider’s remote hands for any physical task, such as reseating, part swaps or console access
• Running GPU node burn-in and diagnostics (DCGM), plus HPL and storage throughput tests with the platform and network engineers
• Planning and executing infrastructure testing, including acceptance testing (ATP), integrated system testing (IST), and high availability, backup and recovery checks
• Checking server-level (L10) test evidence from the manufacturer, recording results against pass/fail thresholds, and raising defects and hardware returns
• Automating server provisioning, configuration push, OS and firmware updates, and test runs and their reports, keeping deployment code in version control with review and testing before it is used on site
• Generating host configuration from the frozen design and site inventory, and keeping that inventory accurate as the source of truth
• Instrumenting automation so every step is timed, giving the data to find the next delay, and feeding lessons learned back into standard playbooks and tooling
• Preparing handover documentation, runbooks and as-built records, supporting Operations during the hypercare window (up to one month), and reporting progress, risks and issues to the Regional Delivery Manager

What We’re Looking For

• 4 to 8+ years’ experience in infrastructure, systems, platform or SRE engineering
• Strong Linux administration and troubleshooting at scale
• Experience with GPU-based systems and workloads
• Strong Kubernetes and container experience, including containerised platforms in production
• Experience with infrastructure-as-code (Terraform, Ansible or similar) and scripting in Python, Go or Bash
• Experience building infrastructure automation, including Git, code review, CI pipelines and bare-metal or cloud provisioning through APIs
• A good understanding of networking and storage
• Bachelor’s degree in Computer Science, Engineering or a related field, or equivalent experience
• Strong communic…