Head of Infrastructure Operations (AI Infrastructure)

Location: United States; remote role with travel to sites in the US and Europe as needed.

Company

hirify.global operates an AI inference platform with custom servers, boards, liquid-cooled inference pods, and a global infrastructure network serving image, video, audio, 3D, and language model workloads.

What you will do

• Build and run infrastructure operations across pod sites, from site bring-up, rack and stack, cabling, power and cooling integration, burn-in, and acceptance through steady-state operations and decommissioning.
• Own Linux, server, storage, networking, provisioning, imaging, firmware, driver, monitoring, and fleet automation layers end to end.
• Define repeatable and automated deployment playbooks for new 1 MW pod sites and improve capacity, reliability, alerting, on-call, incident response, and post-incident processes.
• Hire, lead, and develop data center, systems, and network engineers across time zones.
• Manage colocation, power, connectivity, hardware vendors, capacity contracts, spares, RMA flows, and site-level budgets.
• Partner with hardware and platform engineering on operable designs; use AI agents to automate runbooks, triage, tooling, and operational workflows; own physical infrastructure security and compliance.

Requirements

• 15+ years in infrastructure engineering and operations, including several years leading the function at a company operating its own hardware at scale.
• Experience building infrastructure operations across multiple sites, regions, or countries, including opening data centers, pods, or colocation footprints.
• Deep, current hands-on Linux expertise covering kernel and driver behavior, performance tuning, bare-metal provisioning, configuration management, fleet automation, and node debugging.
• Strong storage fundamentals, including NVMe, distributed and parallel file systems, object storage, throughput, and IOPS for model loading and caching.
• Strong networking fundamentals, including L2/L3 design, BGP, data center fabrics, high-bandwidth interconnects, and network troubleshooting.
• Experience hiring, leading, and retaining strong engineering teams and building effective on-call and incident cultures.
• Daily use of AI for scripting, runbooks, analysis, documentation, and debugging, with a clear operating model for AI-augmented infrastructure teams.
• Ability to own outcomes in a fast-moving, ambiguous environment and remain accountable for uptime, cost, and delivery.
• Ability to travel to sites in the US and Europe as needed.

Nice to have

• Experience operating large GPU fleets for AI training or inference, including NVIDIA drivers, Fabric Manager, NCCL, and GPU health and failure management.
• Experience with RDMA fabrics, including InfiniBand or RoCE, 400G+ Ethernet, and related monitoring tools.
• Experience with liquid-cooled, high-density, modular, or containerized data centers and site-level power and cooling integration.
• Familiarity with server ODMs, component lead times, inventory, spares strategy, and RMA economics.
• Experience with Ansible, Terraform, PXE, image pipelines, IPMI, Redfish, Prometheus, Grafana, or similar observability tools.
• Experience with Kubernetes or Slurm on bare metal and with data residency, sovereignty, or compliance requirements across jurisdictions.

Culture & Benefits

• Remote-first work with in-person meetings twice a year; core collaboration hours are maintained outside a self-managed schedule.
• Meaningful stock options and the mandate, budget, and backing to build global AI infrastructure operations from the ground up.
• Fast release cycles followed by real downtime, with generous paid vacation, sick days, and public holidays.
• Paid maternity, paternity, and caregiver leave.
• Twice-yearly company retreats.