Senior Solutions Architect – AI Infrastructure Networking

• Own network solutioning for k0rdent AI, Mirantis's platform for building and operating GPU clouds and AI factories
• Design interconnects for large GPU clusters, tenant isolation, and network access from containers, virtual machines and bare-metal nodes
• Create and publish reference architectures and solution designs from single-rack to multi-thousand-GPU clusters
• Define InfiniBand and RoCEv2 Ethernet compute fabrics, including rail-optimised and fat-tree/Clos designs
• Define front-end, storage and management networks and connectivity to customer data centers, public clouds and hybrid environments
• Specify multi-tenant isolation using InfiniBand partitions, VRFs, EVPN-VXLAN and Kubernetes network policy
• Document scale limits and trade-offs involving cost, performance, operability and vendor lock-in
• Define Linux host networking and exposure of NICs, DPUs and SuperNICs to workloads
• Design Kubernetes networking for AI workloads, including CNIs, Multus, SR-IOV, RDMA plugins, NVIDIA Network Operator and DRA
• Design KubeVirt networking for GPU and RDMA traffic
• Research emerging AI networking technologies and standards, prototype designs, and measure them against current practice
• Publish research notes, design proposals, papers, blog posts and talks
• Build and run proofs of concept with customers, partners and in Mirantis labs
• Write automation and tooling using Python, Go, Bash, Ansible, Helm, Kubernetes manifests and Terraform
• Validate and benchmark fabrics and host configurations using tools such as NCCL tests, perftest and ib_write_bw
• Act as network subject matter expert in customer discovery, design reviews and architecture workshops
• Collaborate with hardware/networking partners, Solutions Architects, Partner Management, Engineering, Product and customers
• Present at industry events, webinars and partner summits
• Run hands-on technical workshops and write technical enablement content
• Feed research results into Product and Engineering and help shape the k0rdent AI roadmap

• Bachelor's degree in Computer Science, Electrical Engineering, Telecommunications or a related field, or equivalent practical experience
• 8+ years in network engineering or network architecture
• At least 3 years in data center, HPC or cloud infrastructure networking
• Customer-facing experience as a solutions architect, pre-sales engineer, consultant or technical lead
• Data center network design expertise: spine-leaf and Clos topologies, rail-optimised GPU fabrics, oversubscription, ECMP, and scaling to thousands of nodes
• InfiniBand expertise: subnet management, partitioning, adaptive routing, and NCCL/RDMA traffic behavior
• RoCEv2 Ethernet expertise: PFC, ECN, DCQCN, QoS, MTU and buffer tuning
• Routing and overlays: BGP, EVPN-VXLAN and VRFs for multi-tenancy
• Hybrid and multi-cloud connectivity, interconnects, VPN, cloud networking constructs, IP address and DNS planning
• Linux networking, NIC drivers, PCI passthrough, SR-IOV, IOMMU, NUMA affinity, iproute2, ethtool and devlink
• Kubernetes networking: CNI plugins, Multus, SR-IOV and RDMA device plugins, network policy and service exposure
• KubeVirt and VM networking, passthrough and SR-IOV
• Programming or scripting in at least one language; Python or Go preferred
• Comfortable using Git, CI and infrastructure-as-code
• Excellent written and spoken English
• Comfortable presenting to large audiences and running hands-on workshops
• Able to adapt communications for network engineers and customer executives
• Experience working in an international, distributed company across time zones and work cultures
• Up to 25% travel
• Equivalent practical experience may substitute for the bachelor's degree

• Compensation and benefits set according to the local market and employment arrangement
• Remote work arrangement
• Travel opportunities for customer engagements, partner meetings, lab work and industry events (up to 25%)
• Collaboration with a world-class, distributed team
• Opportunity to work directly with leading GPU cloud operators, NeoClouds, sovereign clouds, and AI-first enterprises
• Opportunity to shape the product narrative and influence go-to-market success