GPU Infrastructure Lead - Systems Integrator

Join a pioneering compute infrastructure technology company building the platforms and tools that power the rapidly evolving AI compute market. The organisation develops financial and settlement infrastructure for compute, including technology that connects buyers with GPU capacity, while building automated systems to validate, benchmark, and certify large-scale GPU clusters.

The successful candidate will take end-to-end ownership of the GPU infrastructure function, developing the frameworks and automation used to validate, benchmark, and certify large-scale GPU clusters. Combining hands-on engineering with technical leadership, they will build deployment and testing tooling, establish infrastructure standards, shape technical strategy alongside the founders, and ultimately build and lead the team responsible for the function., * Design and run cluster validation and certification: performance benchmarks, interconnect testing (NCCL, InfiniBand/RoCE), thermal and power verification, availability monitoring against SLAs.

• Build automation for cluster deployment, health checks, and continuous testing so certification scales without headcount scaling with it.
• Set the technical standards for what “deliverable compute” means: node configs, network topologies, storage, cooling envelopes.
• Work directly with capacity providers (neoclouds, data centre operators) during onboarding, from site walkthroughs to acceptance testing.
• Feed what you learn on the ground back into our contract specs, index methodology, and product roadmap.
• Hire and lead the infrastructure engineering team as we grow.

• Experience deploying GPU clusters at varying scales, from smaller node deployments to environments with hundreds or thousands of GPUs, across both air-cooled and liquid-cooled infrastructure. DLC experience is highly advantageous.
• Strong experience troubleshooting complex infrastructure issues, including cabling and topology errors, firmware mismatches, failing optics, thermal throttling, and production performance challenges.
• Experience automating infrastructure-as-code deployments, monitoring and alerting stacks, and hardware acceptance and regression testing.
• Deep familiarity with the NVIDIA technology stack, including HGX platforms, NVLink/NVSwitch, CUDA-level debugging, and NCCL performance tuning.
• Strong leadership skills with the ability to set technical direction, solve complex problems, and guide engineering teams.
• Excellent communication skills with the ability to engage effectively with non-infrastructure stakeholders, including traders, lawyers, capacity providers, and regulators.