ABOUT THE ROLE Location: UK (occasional office travel) | Employment Type: Full-time, Permanent | Reports to: Engineering Manager 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. WHAT YOU'LL DO Infrastructure Design & Virtualisation: - 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. WHAT YOU'LL BRING - 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