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Senior Infrastructure Engineer
Job description
ABOUT THE ROLE
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
- 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/Open. Bao, 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 Infini. Band 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
Description copied from Radiant's careers page. Read the full posting before you apply.
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