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:
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Implement and operate virtualisation solutions optimised for AI-native workloads, including hypervisor tuning for HPC environments.
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Build platform capabilities that scale with customer demand for compute, storage and networking.
Bare-Metal and Operating System Management:
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Deliver provisioning, orchestration and lifecycle management of bare-metal hardware.
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Maintain strong Unix/Linux expertise, producing secure and performant configurations at scale.
Networking and High-Performance Storage:
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Implement high-performance, cloud-native storage and networking for demanding workloads.
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Apply solid working knowledge of networking protocols (TCP, UDP, DNS, encryption) and software-defined networking.
Kubernetes and Cloud-Native Platforms:
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Deploy and manage Kubernetes clusters across hybrid and multi-cloud environments, leveraging CNIs and service meshes.
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Build and maintain CI/CD pipelines that automate infrastructure delivery.
Security and Audit:
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Kubernetes security hardening (RBAC, PSA/PSP successors, network policies, admission controllers - OPA/Gatekeeper, Kyverino)
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Secrets management and rotation across clusters (Vault/OpenBao, sealed-secrets, external-secrets patterns)
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Supply chain security — image scanning, signed artifacts (cosign/sigstore), provenance attestation
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Apply least-privilege IAM patterns across bare-metal, cluster and cloud control planes.
Observability and Automation:
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Build and maintain observability pipelines covering logs, metrics and tracing.
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Create automation frameworks to reduce operational toil, streamline deployments, and enhance scalability using tools like Terraform, Ansible, Go, and Python.
Architecture & Solution Design:
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Analyse emerging technologies and assess their potential fit within our platform, considering scalability, security, and performance.
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Produce low-level designs and implementation plans for platform components, escalating cross-cutting architectural decisions appropriately.
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Collaborate with cross-functional teams to ensure successful implementation of infrastructure solutions.
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Participate in design reviews, offering constructive technical challenge.
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Write clear documentation and runbooks for the systems you build.
Collaboration and Leadership:
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Foster a 'how do we achieve this?' mindset, championing a positive, solution-oriented approach to challenges.
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Mentor less experienced engineers through pairing, code review and design feedback.
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Work with engineers across teams to deliver infrastructure work that lands end to end.
What You'll Bring
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Hands-on experience delivering infrastructure at scale in cloud-native, HPC or AI-native environments.
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Demonstrated success in evaluating and adopting new toolsets and technologies.
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Extensive expertise in large-scale global infrastructure deployments, particularly in AI-native, HPC, and cloud-native environments.
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Strong Kubernetes fundamentals, including container networking (CNI) and service mesh technologies.
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Deep understanding of virtualisation and hypervisor technologies for high-performance workloads.
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Strong proficiency in networking protocols (TCP, UDP, DNS, BGP) and SDN solutions.
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Skilled in Infrastructure-as-Code (IaC) tools like Terraform, Ansible, and cloud orchestration frameworks.
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Hands-on coding experience in Go, Python, or similar languages for automation.
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Solid grasp of observability tools (Prometheus, Grafana) and distributed tracing systems.
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Strong communication and collaboration skills, with the ability to convey complex technical concepts to cross-functional teams.
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Demonstrate ability to create clear and concise documentation for infrastructure designs, processes and systems.
Nice to Have
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AI/ML workloads, GPU-accelerated systems, or HPC infrastructures, including GPU partitioning with MIG and the NVIDIA GPU Operator.
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Experience with RDMA fabrics such as InfiniBand or RoCEv2, and GPUDirect data paths.
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High-throughput distributed storage at scale, such as Ceph or a parallel filesystem.
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Familiarity with hybrid cloud and edge computing principles.
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Experience leading architecture initiatives in agile environments, working iteratively to deliver high-quality results.
Why Join Radiant
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Work on a rapidly scaling AI infrastructure business at the forefront of the industry
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Get broad exposure to a cutting-edge physical & software infrastructure stack
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Be part of a team where you're genuinely valued and your work directly enables business decisions
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Develop your career in a Brookfield-backed company with resources, mentorship, and genuine growth opportunities
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