Senior Solutions Architect – AI Infrastructure Networking (remote in Europe)

Description

You will join the CTO office as a Senior Solutions Architect focused on networking, owning the network design for the company's AI platform, which builds and runs GPU clouds and AI factories from bare metal up to models.

You will work out how large GPU clusters are linked, how tenants are kept apart, and how workloads reach the network from containers, virtual machines and bare metal.

Research is central to this role. You will test designs and technologies before customers ask for them, build prototypes that may never ship, and question accepted practice where something better exists, shaping the platform's future as well as its current deployments.

The work mixes research with hands-on, customer-facing activity: exploring designs, writing architecture, validating it in the lab, and explaining it to engineers, executives and conference audiences. You will work with solutions architects, partner management and engineering across many countries and time zones.

You will work directly with GPU cloud operators, NeoClouds, sovereign clouds and AI-first enterprises, and collaborate with a distributed team focused on openness and technical excellence. You will also help shape the product story and support go-to-market results.

The company is a Kubernetes-native AI infrastructure company. Its platform helps teams build and run scalable, secure, sovereign infrastructure for AI and data-intensive workloads, on premises, in the cloud, at the edge or in sovereign data centers, with open standards and no lock-in.

Responsibilities

• Write and publish network reference architectures and solution designs for the platform, from a single rack up to clusters of several thousand GPUs.
• Design east-west compute fabrics on InfiniBand and RoCEv2 Ethernet, including rail-optimised and fat-tree or Clos layouts, and choose oversubscription and failure domains.
• Design front-end, storage and management networks and their links to customer data centers, public clouds and hybrid setups.
• Define multi-tenant isolation across the stack using InfiniBand PKeys, VRFs, EVPN-VXLAN and Kubernetes network policy.
• Document scale limits and trade-offs in cost, performance, operability and vendor lock-in, with reasoning customers can follow.
• Specify how Linux hosts expose NICs, DPUs and SuperNICs to workloads, covering PCI passthrough, SR-IOV virtual functions, IOMMU groups, NUMA and GPU-NIC affinity.
• Design Kubernetes networking for AI workloads, including primary and secondary CNIs, Multus, SR-IOV and RDMA device plugins, the NVIDIA Network Operator and Dynamic Resource Allocation.
• Design VM networking on KubeVirt, including passthrough and SR-IOV for GPU and RDMA traffic.
• Track and assess emerging AI networking technologies and standards, such as Ultra Ethernet, SuperNIC and DPU offloads, scale-up and scale-across fabrics, and Kubernetes DRA network drivers.
• Prototype alternative designs in the lab, including ones no customer has requested, and benchmark them against current practice.
• Challenge established and customer-preferred designs when evidence favours another option, and back the case with data.
• Publish findings as internal research notes, design proposals and, where suitable, external papers, blog posts or talks.
• Build and run proofs of concept with customers and partners on lab hardware and at customer sites, reporting results against agreed success criteria.
• Write automation and tooling in Python, Go, Bash, Ansible, Helm, Kubernetes manifests or Terraform so the reference architectures can be reproduced.
• Run validation and benchmarks on fabrics and host setups, such as NCCL tests, perftest and ibwritebw, and turn the results into design guidance.
• Act as the network subject matter expert in customer discovery, design reviews and architecture workshops, bringing new ideas as well as current practice.
• Work with hardware and networking partners, such as NVIDIA, server OEMs and switch vendors, on joint designs and validations.
• Feed research results back to product and engineering and help shape the platform roadmap.
• Present at industry events, webinars and partner summits, and run hands-on workshops for technical audiences.
• Write technical content, including reference architecture documents, solution briefs, blog posts and internal enablement material.

Requirements

• Bachelor's degree in computer science, electrical engineering, telecommunications or a related field, or equivalent practical experience.
• At least 8 years in network engineering or architecture, with 3+ years in data center, HPC or cloud infrastructure networking.
• Prior customer-facing work as a solutions architect, pre-sales engineer, consultant or technical lead.
• Data center design: spine-leaf and Clos topologies, rail-optimised GPU fabrics, oversubscription, ECMP, and the operational challenges of running thousands of nodes.
• InfiniBand: subnet management, partitioning, adaptive routing, and how NCCL and RDMA traffic behaves on the fabric.
• RoCEv2 on Ethernet with lossless, congestion-controlled designs: PFC, ECN, DCQCN, QoS, MTU and buffer tuning.
• Routing and overlays: BGP, EVPN-VXLAN and VRFs used for multi-tenancy.
• Hybrid and multi-cloud connectivity: interconnects, VPNs, cloud provider networking constructs, and IP and DNS planning across sites.
• Linux networking: how the kernel and drivers manage NICs, PCI passthrough, SR-IOV, IOMMU and NUMA affinity, and tools such as iproute2, ethtool and devlink.
• Kubernetes networking: CNI plugins such as Cilium, Calico and OVN-Kubernetes, Multus, secondary networks, SR-IOV and RDMA device plugins, network policy and service exposure.
• KubeVirt, including how VM networking, passthrough and SR-IOV are configured.
• Programming or scripting in at least one language, Python or Go preferred, and comfort with Git, CI and infrastructure-as-code.
• Curiosity: you dig into why fabrics behave as they do, read specs and source code, and keep up with how AI networking is changing. You question established designs, including customers' preferred ones, when a better option exists.
• Ownership: you take a reference architecture or proof of concept from first sketch to a published, validated result and stand behind it.
• Initiative: you spot gaps in the product, the documentation or a customer design before being asked, and act on them.
• Quick learning: you become productive fast on unfamiliar hardware, software or customer environments.
• Business sense: you tie network choices to cost, time-to-value and risk, and explain them in those terms to decision makers.
• Excellent written and spoken English, and you write documents others can build from.
• Comfortable presenting to large audiences and running hands-on workshops.
• Able to adapt the message to the audience, from network engineers to customer executives.
• Experience in an international, distributed company across time zones and work cultures, with solutions architects, partner management and engineering teams.
• Hands-on NVIDIA networking experience: Quantum InfiniBand, Spectrum-X Ethernet, ConnectX SuperNICs, BlueField DPUs, UFM and NVIDIA reference designs for AI factories.
• Experience with GPU cloud, neocloud or HPC operators, or with NVIDIA Cloud Partner style deployments.
• Bare-metal provisioning and lifecycle: Metal3, Ironic, Redfish, PXE or iPXE, and Cluster API.
• Network automation, SDN controllers, and switch operating systems such as Cumulus Linux, SONiC or vendor equivalents.
• Global load balancing and service exposure for distributed inference: GSLB, Gateway API and ingress.
• Software-defined storage networking for AI: NVMe-oF and GPUDirect Storage.
• Experience with the company's own Kubernetes products and their networking.
• Open-source networking or Kubernetes contributions, or a track record of public talks and technical writing.
• Participation in standards or industry bodies such as the Ultra Ethernet Consortium, OCP or IETF, or published research, patents or white papers.
• Additional languages beyond English, for example a European language.

Conditions

This is a remote role, open to candidates based in Europe.

The team spans many time zones, so some meetings fall outside standard local hours.

Travel of up to 25% for customer engagements, partner meetings, lab work and industry events, mainly within the EU and US.

Equal opportunity employer; pay and benefits follow the local market and employment arrangement, and the company may use automated decision-making in employment decisions, which you can opt out of or appeal.