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Verda

Full-stack AI cloud with GPU compute

Kubernetes and Container Platform Security Specialist

Security Engineering & ArchitectureUpdated on Nov 10
Full-timeNo salary listed

About the Job

Requirements

  • Strong production Kubernetes and Linux experience at a depth that enables identifying security problems, not merely configuring around them.
  • Direct experience with multi-tenant Kubernetes, including shared clusters, untrusted workloads, and isolation as a requirement.
  • Deep understanding of Kubernetes architecture, the container runtime layer, and container and image security.
  • Strong Kubernetes networking skills, including CNI-level policy design.
  • Practical experience with policy-as-code and admission control, and working knowledge of software supply chain security, including signing, provenance, software bills of materials, and admission-time enforcement requirements.
  • Ability to write standards for others to implement, verify conformance without owning the change, and influence an engineering team the candidate does not manage.
  • A research mindset involving testing new technology, finding weaknesses, building proofs of concept, and turning findings into requirements that ship.
  • Comfort operating with incomplete information and making decisions quickly.

Responsibilities

  • Own the security design of Verda's Kubernetes offering, container registry, and registry credentials, including image provenance, signing, and admission verification requirements.
  • Own the tenant isolation model on shared Kubernetes infrastructure, covering namespace, node, and cluster boundaries, tenant reachability, and kubelet and API server exposure.
  • Own the GPU-specific security surface, including device plugins, privileged operator workloads, and partitioning boundaries.
  • Define the Kubernetes hardening baseline across the control plane, node operating system, container runtime, etcd, and secrets handling, along with the policy and admission enforcement model, expressed as policy-as-code so conformance is continuously observable.
  • Design the Kubernetes network security model with Network Security, including CNI-level policy, L3/L4/L7 controls, DNS, and egress policy.
  • Specify runtime detection requirements for the Security Operations Center to operate and triage, scope assessments and attack simulations for red teams to execute, and act on findings from both.
  • Assess Kubernetes and container ecosystem advisories against Verda's configuration and set remediation priorities; research new releases and ecosystem technology in a lab before production adoption; and support Verda's compliance position through technical evidence and audit support.

Desired Qualifications

  • Experience with GPU infrastructure, including device plugins, GPU operators, partitioning, and the privileged workloads they require.
  • Experience operating multi-tenant container registries at scale.
  • Experience with eBPF-based observability or runtime security.
  • Experience with cluster lifecycle and fleet management tooling.
  • Experience with CVE analysis, advisory triage, or upstream contributions in the Kubernetes or CNCF ecosystem.
  • Experience with confidential computing or attested execution environments.
  • Experience in cloud provider, hosting, or another environment where the infrastructure is the product, ideally one certified to ISO 27001, SOC 2, or C5 where the candidate produced the technical evidence.

About the Company

Verda

Full-stack AI cloud with GPU compute

Verda provides a full-stack AI cloud infrastructure in Europe and beyond, combining the physical data centers and hardware with a cloud platform and AI research capabilities. It offers on-demand and reserved GPU instances, serverless containers, and managed inference on vertically integrated European infrastructure powered by renewable energy. The company serves AI and software teams who need self-service compute without long sales cycles. Verda is an NVIDIA Preferred Partner and operates across Europe, the UK, the US, and Asia. Its goal is to multiply compute capacity, deepen inference and platform services, and expand internationally while maintaining a strong growth trajectory.

Company size
201-500
Company stage
Series B
Total funding
$513.7M
Headquarters
Helsinki, Finland
Founded
2020

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