About XENON
XENON designs and builds the AI factories — the dense, GPU-accelerated compute, storage and networking environments — that power large-scale research, training and inference for leading organisations across the country.
The role
We’re hiring a Senior Platform Engineer to build and operate the GPU infrastructure platform that empowers our customers to run their most demanding AI and HPC workloads. You’ll own the full stack — Kubernetes and HPC scheduling, GPU fabric and node lifecycle, infrastructure-as-code and observability — working directly with XENON architects, ML/platform teams and customers to keep large-scale, multi-tenant GPU environments fast, reliable and secure.
What you’ll do
- Manage high-performance GPU clusters using Kubernetes and/or HPC schedulers such as Slurm, including node lifecycle management and cluster scaling.
- Design and deploy leaf-spine GPU fabrics — NVIDIA Cumulus Linux, InfiniBand and RoCE/RDMA — tuned for low-latency, lossless GPU-to-GPU traffic.
- Build and maintain Infrastructure-as-Code (Terraform, Ansible) to automate provisioning, scaling and configuration across the platform.
- Improve GPU utilisation, scheduling efficiency and infrastructure cost, and build out observability — monitoring, logging and alerting.
- Ensure high availability, fault tolerance and disaster recovery, and implement security controls and workload isolation across multi-tenant environments.
- Partner with ML and platform teams to optimise infrastructure for training and inference workloads, and contribute to capacity planning.
- Provide L3 support for complex platform and fabric incidents, lead root cause analysis, and drive ongoing reliability improvements.
What you bring
- 6–10+ years in infrastructure engineering, platform engineering, SRE or HPC/network engineering, operating distributed systems at scale.
- Strong hands-on Kubernetes and container orchestration experience, plus HPC scheduler experience (Slurm, PBS, LSF or similar).
- Experience managing or optimising GPU-based systems and AI/deep learning stacks (TensorFlow, PyTorch, CUDA).
- Hands-on experience with InfiniBand and/or NVIDIA Cumulus Linux fabrics — BGP, EVPN, VXLAN and RoCE/RDMA for GPU-to-GPU traffic (NCCL-aware a strong plus).
- Strong Infrastructure-as-Code skills (Terraform, Ansible) and programming/scripting in Python, Go and/or Bash.
- Experience with high-performance storage and networking systems: Ceph, Lustre, Spectrum Scale/GPFS, Weka or BeeGFS.
- Cloud architecture experience across AWS and/or Azure — technical certification highly regarded.
- Strong observability and performance-tuning capability, with a proven ability to optimise for cost, performance and efficiency.
- A security-first mindset and knowledge of infrastructure hardening practices.
- Strong communication, collaboration and technical leadership skills. Computer Science or Engineering degree, or equivalent experience.
Why XENON
- Own the full stack of next-generation AI factories — compute, fabric and platform — not legacy enterprise IT.
- Direct exposure to the latest NVIDIA, Kubernetes and cloud platforms as they ship.
- A small, senior team where your designs go straight into production for Australia’s leading research and AI organisations.
- Competitive salary, plus training and certification support to stay current on a fast-moving stack.
Diversity and Inclusion
XENON is committed to creating a diverse environment that embraces differences and fosters inclusion.
Equal Opportunity
XENON is an Equal Opportunity Employer and strongly committed to all policies which will afford equal opportunity employment to all qualified persons without regard to age, national origin, race, ethnicity, creed, gender, disability, veteran status, or any other characteristic protected by law.
Apply
Please complete the form below and tell us about the largest GPU platform or fabric you’ve built or operated. Tell us about the problem, your approach, and the outcome — that’s what we care about most.