Senior Infrastructure Engineer

We’re looking for a Senior Infrastructure Engineer in our Platform team to drive the architecture, design, and implementation of our next-generation AI-native cloud platform. You will implement scalable, resilient infrastructure and the self-service tooling that sits on top of it, working within an agreed architectural direction and contributing to how that direction evolves. You will combine strong hands-on engineering with clear communication, enabling teams to run HPC and AI/ML workloads reliably at scale., * Implement and operate virtualisation solutions optimised for AI-native workloads, including hypervisor tuning for HPC environments.

• Build platform capabilities that scale with customer demand for compute, storage and networking.

Bare-Metal and Operating System Management:

• Deliver provisioning, orchestration and lifecycle management of bare-metal hardware.
• Maintain strong Unix/Linux expertise, producing secure and performant configurations at scale.

Networking and High-Performance Storage:

• Implement high-performance, cloud-native storage and networking for demanding workloads.
• Apply solid working knowledge of networking protocols (TCP, UDP, DNS, encryption) and software-defined networking.

Kubernetes and Cloud-Native Platforms:

• Deploy and manage Kubernetes clusters across hybrid and multi-cloud environments, leveraging CNIs and service meshes.
• Build and maintain CI/CD pipelines that automate infrastructure delivery.

Security and Audit:

• Kubernetes security hardening (RBAC, PSA/PSP successors, network policies, admission controllers - OPA/Gatekeeper, Kyverino)
• Secrets management and rotation across clusters (Vault/OpenBao, sealed-secrets, external-secrets patterns)
• Supply chain security - image scanning, signed artifacts (cosign/sigstore), provenance attestation
• Apply least-privilege IAM patterns across bare-metal, cluster and cloud control planes.

Observability and Automation:

• Build and maintain observability pipelines covering logs, metrics and tracing.
• Create automation frameworks to reduce operational toil, streamline deployments, and enhance scalability using tools like Terraform, Ansible, Go, and Python.

Architecture & Solution Design:

• Analyse emerging technologies and assess their potential fit within our platform, considering scalability, security, and performance.
• Produce low-level designs and implementation plans for platform components, escalating cross-cutting architectural decisions appropriately.
• Collaborate with cross-functional teams to ensure successful implementation of infrastructure solutions.
• Participate in design reviews, offering constructive technical challenge.
• Write clear documentation and runbooks for the systems you build.

Collaboration and Leadership:

• Foster a ‘how do we achieve this?’ mindset, championing a positive, solution-oriented approach to challenges.
• Mentor less experienced engineers through pairing, code review and design feedback.
• Work with engineers across teams to deliver infrastructure work that lands end to end.

• Hands-on experience delivering infrastructure at scale in cloud-native, HPC or AI-native environments.
• Demonstrated success in evaluating and adopting new toolsets and technologies.
• Extensive expertise in large-scale global infrastructure deployments, particularly in AI-native, HPC, and cloud-native environments.
• Strong Kubernetes fundamentals, including container networking (CNI) and service mesh technologies.
• Deep understanding of virtualisation and hypervisor technologies for high-performance workloads.
• Strong proficiency in networking protocols (TCP, UDP, DNS, BGP) and SDN solutions.
• Skilled in Infrastructure-as-Code (IaC) tools like Terraform, Ansible, and cloud orchestration frameworks.
• Hands-on coding experience in Go, Python, or similar languages for automation.
• Solid grasp of observability tools (Prometheus, Grafana) and distributed tracing systems.
• Strong communication and collaboration skills, with the ability to convey complex technical concepts to cross-functional teams.
• Demonstrate ability to create clear and concise documentation for infrastructure designs, processes and systems.

Nice to Have

• AI/ML workloads, GPU-accelerated systems, or HPC infrastructures, including GPU partitioning with MIG and the NVIDIA GPU Operator.
• Experience with RDMA fabrics such as InfiniBand or RoCEv2, and GPUDirect data paths.
• High-throughput distributed storage at scale, such as Ceph or a parallel filesystem.
• Familiarity with hybrid cloud and edge computing principles.
• Experience leading architecture initiatives in agile environments, working iteratively to deliver high-quality results.

Why Join Radiant

• Work on a rapidly scaling AI infrastructure business at the forefront of the industry
• Get broad exposure to a cutting-edge physical & software infrastructure stack
• Be part of a team where you’re genuinely valued and your work directly enables business decisions
• Develop your career in a Brookfield-backed company with resources, mentorship, and genuine growth opportunities