We are a technology consulting firm building and operating next-generation AI supercompute infrastructure for the world's most ambitious organizations. As Platform Engineer, you will work hands-on across the full infrastructure stack with a particular focus on the physical and logical networking layer that makes large-scale GPU clusters perform at their theoretical limits.
As a repeatedly awarded NVIDIA Consulting Partner of the Year in EMEA, we hold one of the deepest and most recognized NVIDIA partnerships in the region. This gives our engineers privileged access to adoption programmes and NVIDIA's engineering teams.
You will work with technology and at a scale that most engineers won't encounter for years.
This is a role for someone at a mid-career stage in platform or infrastructure engineering. You have solid foundations and real hands-on experience, and you are ready to level up by working on problems of genuine complexity and scale. You know enough to know what you don't know yet, and you are hungry to close that gap fast.
What We Expect
5–8 years of hands-on experience in infrastructure, networking, or systems engineering
Solid understanding of networking fundamentals: OSI model, switching and routing (BGP, OSPF), VLANs, MTU, and traffic engineering
Working knowledge of high-performance networking technologies: InfiniBand, RDMA, RoCE, or equivalent HPC interconnects
Familiarity with Linux networking: interfaces, bridges, bonding, namespaces, tc/qdisc, and kernel network tuning
Basic hands-on experience with Kubernetes or Slurm: enough to navigate cluster operations, understand pod scheduling, and troubleshoot node-level issues
Experience with at least one monitoring stack: Prometheus, Grafana, Zabbix, or similar
Experience with network automation and IaC
Comfort working directly with physical hardware: servers, switches, cabling and data centre environments
Bonus Experience
Exposure to NVIDIA networking products: Mellanox/ConnectX NICs, Quantum InfiniBand switches, Spectrum Ethernet switches
Familiarity with NCCL tuning, collective communication patterns, or distributed training networking requirements
Hands-on time with DCGM, iperf3, perftest, or ibdiagnet for infrastructure benchmarking and validation
Exposure to container networking
Any experience in a consulting or client-facing technical role