Director, Infrastructure Engineering

The role

You will lead and scale core cloud and bare-metal environments including SRE, global networking, HPC networks, and distributed storage engines. You will build the technical direction and culture to ensure high availability and scalability for AI workloads.

What you will do

• Lead multiple engineering teams responsible for SRE, networking, and storage.
• Oversee the design, scaling, and operation of the global network backbone and HPC cluster networks.
• Direct the architecture and performance tuning of distributed storage systems.
• Hire, mentor, and grow engineering managers and senior ICs.
• Partner with Program Management and Product to forecast capacity and shape technical roadmaps.
• Drive improvements in infrastructure reliability and delivery metrics.
• Provide architectural oversight for bare-metal provisioning, virtualization, network fabrics, and storage clusters.
• Coordinate with product delivery and platform teams.

Required qualifications

• 7+ years leading software, infrastructure, SRE, or networking teams, including managing managers and multiple squads.
• 8+ years building and operating large-scale distributed systems, bare-metal infrastructure, or public/private cloud platforms.
• Proven hands-on background or strong architectural understanding of ultra-low latency networking.
• Deep familiarity with InfiniBand and/or RoCE, spine-leaf architectures, and global WAN routing protocols (BGP).
• Experience building, operating, or tuning high-performance distributed storage systems and parallel file systems (e.g., Ceph, Lustre, Weka, NVMe-oF).
• Strong foundation in reliability engineering, infrastructure-as-code (Terraform, Ansible), container orchestration (Kubernetes), and modern observability stacks.
• Experience building culture, accountability, and momentum across distributed technical teams.
• Clear written and verbal communication.
• Strong stakeholder management.
• Calm, decisive leadership during high-stakes operational incidents.

Nice to have

• Direct experience architecting and operating infrastructure specifically optimized for massive GPU clusters and AI/ML workloads.
• Deep understanding of hardware architectures, GPU interconnects (NVLink), and datacenter topology.
• Track record of scaling infrastructure teams in hyper-growth startup environments.
• Open-source contributions or active recognition within the infrastructure, networking, or Kubernetes communities.

Benefits

• Competitive base pay
• Stock options
• Generous medical, dental & vision plans
• Flexible PTO
• $1,200 Home Office & Equipment Stipend

Before you apply

• Successful completion of a background check
• We are currently unable to sponsor employment visas

About the company

Runpod is the AI Developer Cloud used by more than one million developers to experiment, train, fine-tune, deploy, and scale AI. It is a small, remote-first team.