Infrastructure Lead (AI)

Location: Remote internationally, with remote hiring possible in most countries; in-person work is available in Berkeley, California or Singapore. Working hours should preferably overlap with Berkeley.

Salary: $225K–$325K annually, adjusted for location and experience.

Company

hirify.global is a nonprofit AI research institute focused on advancing AI safety research and coordinating global responses to AI risks.

What you will do

• Set the technical direction and roadmap for a multi-provider GPU cluster platform supporting frontier AI research.
• Own architecture for scheduling, storage, networking, infrastructure as code, security, observability, and platform operations.
• Debug failures across GPU nodes, fabrics, storage, scheduling, and multi-node workloads.
• Hire, grow, and coach a small team of senior infrastructure engineers.
• Define incident response, on-call, postmortem, fault-tolerance, and operational practices.
• Act as the escalation point for research teams and infrastructure providers, turning recurring issues into platform improvements.

Requirements

• Leadership experience as an engineering manager, technical lead, or project lead, including technical direction, prioritization, and feedback.
• At least 5 years of systems or infrastructure engineering experience with production Linux and GPU, HPC, or large-scale batch platforms.
• Production Kubernetes experience for GPU workloads with a batch layer such as Slurm, Kueue, or Volcano.
• Experience with infrastructure as code and observability using tools such as Terraform, Ansible, Helm, ArgoCD, and Prometheus.
• Strong programming ability in Python, Go, Rust, C++, or a comparable infrastructure language.
• For in-person employees, visa sponsorship is available; remote hiring is possible in most countries.

Nice to have

• Experience with distributed training infrastructure, PyTorch, NCCL, NVIDIA GPU systems, InfiniBand, or RoCE.
• Experience with distributed storage systems such as VAST, Weka, Lustre, Ceph, or large-scale object storage.
• Experience with cluster security, sandboxed runtimes, scheduler internals, or multi-provider platforms.
• Experience building a new team and establishing on-call, incident, and review practices.

Culture & Benefits

• Work directly with AI researchers and engineers on large-scale, fault-tolerant experiments.
• Remote and in-person work options are available, with working-hours overlap with Berkeley preferred.
• Full-time schedule of 40 hours per week with participation in incident coverage as the platform grows.
• US employees receive health insurance support, a 401(k) plan with up to a 2% match, paid time off, paid leave, equipment, and a work-from-home stipend.
• International employees receive benefits through an EOR or contractor arrangement, depending on location.

Hiring process

• Programming assessment and screening call.
• Code review, systems design and incident response, and management and leadership interviews.
• Paid work trial lasting up to one week, with alternative evaluation options when needed.