Senior Infrastructure Engineer

Radiant
London, United Kingdom
Hybrid

Who this role is best for

Best suited to experienced engineers with deep cloud-native and HPC expertise working in a collaborative, technically ambitious environment.

Best fit for

  • Candidates with experience in large-scale AI-native and HPC infrastructure deployments and strong Kubernetes expertise
    — “Strong Kubernetes fundamentals, including container networking (CNI) and service mesh technologies”
  • Individuals who have led infrastructure architecture initiatives in agile teams and demonstrated technical leadership
    — “Experience leading architecture initiatives in agile environments, working iteratively to deliver high-quality results”
  • Engineers with a track record of building automation frameworks for infrastructure delivery
    — “Create automation frameworks to reduce operational toil, streamline deployments, and enhance scalability using tools like Terraform, Ansible, Go, and Python”

Things to consider

  • Occasional office travel may be necessary despite remote flexibility
    — “Location: UK (occasional office travel)”
  • The role requires hands-on coding skills in Go or Python for automation
    — “Hands-on coding experience in Go, Python, or similar languages for automation”

How to stand out

  • Emphasize experience with Kubernetes security hardening and observability tooling in your resume and interviews
    — “Kubernetes security hardening (RBAC, PSA/PSP successors, network policies, admission controllers - OPA/Gatekeeper, Kyverino)”
  • Highlight your ability to create clear documentation and runbooks for complex systems
    — “Write clear documentation and runbooks for the systems you build”
  • Showcase your work with high-performance storage and networking in cloud-native environments
    — “Implement high-performance, cloud-native storage and networking for demanding workloads”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Successfully implemented and operated virtualisation solutions for AI-native workloads
  • Built and maintained CI/CD pipelines for infrastructure delivery
  • Deployed and managed Kubernetes clusters across hybrid and multi-cloud environments
Typical background
Experience in delivering infrastructure at scale in cloud-native, HPC or AI-native environmentsStrong Unix/Linux expertiseExperience in evaluating and adopting new toolsets and technologies

Skills & requirements

Required

C++GoLinuxWindowsMultithreadingSTLObject-oriented ProgrammingKubernetesCi/cd PipelinesTerraformAnsiblePythonKubernetes SecurityRBACNetwork PoliciesAdmission ControllersSecrets ManagementObservability PipelinesLogs

Preferred

C#JavaDockerAWSAzureGCP

Stack & domain

Virtualisation SolutionsHypervisor TuningCloud-native Storage And NetworkingNetworking ProtocolsSoftware-defined NetworkingKubernetes ClustersCi/cd PipelinesKubernetes Security HardeningSecrets ManagementSupply Chain SecurityObservability PipelinesAutomation FrameworksTerraformAnsibleGoPythonEmerging TechnologiesScalabilitySecurityPerformanceDesign ReviewsDocumentation And RunbooksCommunicationLeadershipMentoringCollaborationTechnical ChallengeSolution-oriented ApproachAi-native Cloud PlatformHPCAi/ml WorkloadsCloud-nativeHybrid And Multi-cloud EnvironmentsInfrastructure Solutions

About the role

Original posting from Radiant via Ashby

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

Source: Radiant careers (Ashby)

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