Head of Artificial Intelligence

The role: Now seeking a talented Head of AI Infrastructure. This is the company's first dedicated infrastructure hire, reporting directly to the CTO.You'll start as a senior individual contributor, hands-on and owning the AI platform end to end: compute, memory, network, storage, orchestration and field operations. You'll also be the senior technical voice for customers and set the 12 to 18 month infrastructure roadmap.

The team: Over the first 6 to 12 months, as pods deploy across metros, you'll hire engineers across platform/SRE, networking, storage and field operations, then add managers as the fleet grows. Cloud infrastructure, IT and security sit with the VP of IT & Security. Properties and installation, and vendor management, have their own teams. You'll partner closely with all three.

What you'll do: Bring up, burn in and run GPU pods in production, and own the acceptance benchmarks every new pod and hardware generation must pass Measure and improve inference performance across compute, memory, network and storage: tokens per second per kW, KV-cache offload, RoCEv 2 and NCCL fabric performance, model cold-start Test and roll out frequent driver, vLLM and model updates safely, with clear benchmarks and rollback plans Run power-aware operations: GPU power caps, curtailment and workload drain coordinated with other on-site energy loads Design for graceful failure, so work hands off cleanly between pods and sites Operate a multi-tenant, bare-metal Kubernetes GPU platform against service level objectives, with 24/7 incident response Write the runbooks field technicians follow at unmanned sites Act as technical lead for customers, and set the 12 to 18 month infrastructure roadmap Hire and lead a team across platform/SRE, networking, storage and field operations as the fleet scales What you'll bring 12+ years in infrastructure, with hands-on ownership of physical production compute at scale (not only consuming public cloud services)Experience at a hyperscaler, GPU cloud or neocloud: you know how large organizations keep large systems running Depth in at least two of: inference serving (such as vLLM), Infini Band or RoCE networking, distributed storage, bare-metal Kubernetes Strong Linux skills, plus Python or Go: you read the code and write the fix Happy to start as a hands-on individual contributor, with the ambition to build and lead a team

Nice to have: Large-scale GPU cluster management (1,000+ GPUs)Power-aware scheduling, GPU power capping or demand response Edge infrastructure, such as CDN points of presence, cloud local zones or telecom edge Building AI compute infrastructure from the ground up Background at a GPU, chip or infrastructure vendor, such as NVIDIA, AMD, Intel or Oracle You don't need to check every box to be considered. Why join Permitted, grid-connected power is already in place across a nationwide property network, so pods deploy in weeks rather than years The first infrastructure hire, reporting to the CTO, shaping the platform and the team from day one

Travel: occasional travel to pod sites and customers Work authorization: must already be authorized to work in the US or Canada; visa sponsorship is not available

Compensation: competitive base salary, bonus and equity included