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Platform Engineer (7351A69)

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The Role
You will help design, build and operate the on-premises Kubernetes platform that sits beneath the firm's application workloads — from the hypervisor and VM provisioning up through Kubernetes cluster lifecycle, networking, storage and the golden-path tooling application teams use to ship software. The Linux VM fabric (KVM/libvirt-based) is still being designed and built out, so you will have real influence over its architecture, not just its day-to-day operation, and you will keep the fabric and the clusters running on top of it healthy, secure and performant without the safety net of a hyperscaler's managed control plane.
Your work will span the full stack: designing the VM fabric's hypervisor architecture, host networking topology and storage backing; designing and maintaining distributed shared storage such as Ceph; building VM templating and golden-image pipelines; automating the VM lifecycle end to end via infrastructure-as-code; and managing capacity planning, oversubscription strategy and headroom for failure or maintenance. You will own virtual networking within the fabric and its clean handoff into the Kubernetes CNI layer; design, build and maintain the full lifecycle of on-prem Kubernetes clusters (bootstrapping, version upgrades, node scaling, decommissioning) using tooling such as kubeadm, Cluster API or Kubespray; manage the control plane end to end, including etcd operations, backup/restore, performance tuning and disaster recovery; configure CNI, network policy enforcement and on-prem load balancing; stand up ingress and internal DNS; and own persistent storage integration via CSI drivers. You will define and enforce multi-tenancy patterns across both layers, build GitOps-based delivery with ArgoCD or Flux, harden hosts and clusters against CIS benchmarks, manage secrets, build observability across the full stack from hypervisor health to cluster metrics and logs, plan and execute upgrades with minimal workload disruption, troubleshoot incidents from a misbehaving pod down through kubelet, the container runtime and CNI into the underlying VM and hypervisor, share an on-call rotation for platform-level incidents, partner with application teams on developer experience, and coordinate with datacentre and network teams on physical host provisioning.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What We're Looking For
- Solid production experience running Kubernetes in a self-managed, on-premises context (not just EKS/GKE/AKS) — you understand what breaks when there's no managed control plane, and you've operated etcd and the control plane yourself
- Hands-on experience designing and operating a Linux KVM/libvirt-based VM fabric as the foundation for Kubernetes, ideally from a relatively early stage rather than just inheriting a mature environment
- Strong Linux systems administration background: networking, storage, service management, kernel tuning and troubleshooting under pressure
- Practical, in-depth knowledge of Kubernetes networking (CNI internals; service meshes a plus) and storage (CSI drivers, distributed storage systems such as Ceph/Longhorn)
- Experience with infrastructure-as-code and configuration management (Terraform, Ansible, Packer), GitOps workflows and CI/CD pipelines
- Comfortable with observability stacks (Prometheus/Grafana, ELK/Loki) and using them to diagnose infrastructure issues without cloud-native tooling
- Security-conscious: familiar with hardening standards, RBAC, network segmentation and secrets management
- Strong troubleshooting instincts across the full stack — hypervisor, OS, network, container runtime, Kubernetes control plane — and good written and verbal communication with distributed or hybrid teams


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Relevant Desirable Experience
- Bare-metal Kubernetes provisioning; a background in a regulated or air-gapped/restricted-network environment
- Contributions to open-source infrastructure tooling
- Using AI tooling to accelerate development; experience running AI infrastructure
This could suit an infrastructure or platform engineer who likes understanding systems all the way down — from hypervisor to pod — and wants real ownership with no black-box managed services standing between them and root cause.
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