Architect of Platform Engineering – AI Supercompute Infrastructure | Cloud & Engineering

We are a technology consulting firm building and operating next-generation AI supercompute infrastructure for the world's most ambitious organizations. As Architect of Platform Engineering, you will own the full stack, from bare metal and operating system up through cluster orchestration, job scheduling, and observability across engagements with leading enterprise and public sector clients pushing the frontier of AI adoption. 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 programs and NVIDIA's engineering teams. You will work with technology and at a scale that most engineers won't encounter for years. This role sits at the intersection of deep technical ownership and client-facing leadership. You will shape platform strategy for clients, embed within their teams, and deliver outcomes that define how large-scale AI infrastructure is built and run. You will work in close partnership with NVIDIA to bring cutting-edge GPU architecture and software capabilities directly to client environments. We are looking for a hands-on technical Architect who thrives in entrepreneurial, high-velocity environments. What We Expect: 8+ years of hands-on infrastructure and platform engineering experience, including full ownership of production systems cluster architecture, control plane operations, custom controllers/operators, multi-tenancy, and large-scale fleet management Slurm experience or other HPC/AI workload scheduling: job queuing, fair-share scheduling, MPI integration Strong Linux internals knowledge: kernel tuning, cgroups, namespaces, NUMA topology, hugepages, and storage subsystems Familiarity with high-speed networking: InfiniBand, RoCE, RDMA; tuning for distributed training workloads Infrastructure as Code fluency: Terraform, Ansible, Helm or equivalent Demonstrated ability to lead technical engagements with enterprise clients. Translating ambiguous requirements into clear deliverables, managing stakeholders across seniority levels, and navigating complex organizational dynamics Entrepreneurial mindset. Comfortable operating with autonomy and moving fast without sacrificing rigor Bonus Experience Proven experience managing NVIDIA GPU infrastructure: driver lifecycle, CUDA toolchain, MIG/MPS partitioning, NVLink/NVSwitch topologies, and GPUDirect RDMA Familiarity with NVIDIA Base Command Platform, DGX SuperPOD, or CSP GPU cloud deployments Experience with DCGM, or other GPU profiling and telemetry tooling Prior consulting, professional services, or client delivery experience in an infrastructure or cloud practice Contributions to open-source platform tooling or CNCF ecosystem projects Apply To This Job