Director of Infrastructure Engineering

Runpod is the AI Developer Cloud. More than one million developers from indie researchers to teams running frontier models in production use Runpod to experiment train fine-tune deploy and scale AI on one platform. The platform has processed more than 20 billion inference requests. We closed a $100M Series A in June 2026. We're at an inflection point for AI infrastructure and we're building the platform the next generation of developers will depend on. We're a small remote-first team. We take ownership seriously move fast and ship work that more than a million developers rely on every day. We're looking for people who care deeply build with urgency and want to matter at scale.

Learn more in our CEO's funding announcement: https://www.runpod.io/blog/one-million-developers.

We’re looking for a Director of Infrastructure Engineering to lead and scale Runpod’s core cloud and bare-metal environments. This role owns the critical foundational layers of our platform—Site Reliability Engineering (SRE) global networking High-Performance Computing (HPC) networks and distributed storage engines. You’ll build the operating rhythm culture and technical direction that ensures Runpod remains highly available performant and capable of scaling to meet massive GPU computing demands.

You will partner tightly with Product Engineering Product and GTM leadership to support enterprise customers. Your focus is ensuring that our underlying infrastructure provides the absolute fastest most reliable and lowest-latency path for customers training and running large-scale AI workloads.

Responsibilities:

• Own Core Infrastructure & SRE: Lead multiple engineering teams responsible for Site Reliability Engineering networking and storage. Establish rigorous SRE practices driving SLA/SLO definitions incident response observability and automated remediation.

• Architect HPC & Global Networking: Oversee the design scaling and operation of Runpod’s global network backbone as well as ultra-low-latency HPC cluster networks. Drive the implementation and optimization of InfiniBand and RDMA over Converged Ethernet (RoCE) to support massive multi-node GPU training workloads.

• Drive Storage Engine Innovation: Direct the architecture and performance tuning of highly scalable distributed storage systems. Ensure our storage engines can deliver the massive IOPS and throughput required to keep high-end GPUs fed with data during deep learning tasks.

• Build a High-Output Org: Hire mentor and grow highly technical engineering managers and senior ICs (network architects systems engineers SREs). Create a culture of ownership operational excellence and craft in a remote-first environment.

• Translate Scale into Strategy: Partner with Program Management and Product to forecast capacity requirements shape technical roadmaps and convert massive scale challenges into clear technical scopes milestones and measurable outcomes.

• Continuously Improve Systems & Flow: Drive measurable improvements in infrastructure reliability and delivery metrics such as deployment frequency MTTR (Mean Time To Recovery) infrastructure as code (IaC) coverage and system uptime.

• Architectural Stewardship: Provide architectural oversight for bare-metal provisioning virtualization layers network fabrics and storage clusters ensuring seamless scalability without becoming a bottleneck for your teams.

• Cross-Functional Partnership: Coordinate cleanly with product delivery and platform teams to ensure the infrastructure primitives they rely on are robust well-documented and highly available.

Requirements:

• Engineering Leadership Experience: 7+ years leading software infrastructure SRE or networking teams including managing managers and multiple squads with a proven record of scaling high-availability cloud environments.

• Deep Infrastructure Expertise: 8+ years building and operating large-scale distributed systems bare-metal infrastructure or public/private cloud platforms.

• HPC & Advanced Networking: 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).

• Storage Systems Knowledge: Experience building operating or tuning high-performance distributed storage systems and parallel file systems (e.g. Ceph Lustre Weka NVMe-oF) capable of handling heavy AI/ML I/O loads.

• SRE / DevOps Culture: Strong foundation in reliability engineering infrastructure-as-code (Terraform Ansible) container orchestration (Kubernetes) and modern observability stacks.

• Remote-First Operating Excellence: Experience building culture accountability and momentum across distributed technical teams.

• Communication & Collaboration: Clear written and verbal communication strong stakeholder management and calm decisive leadership during high-stakes operational incidents.

• Background Check: Successful completion of a background check.

Preferred Qualifications:

• 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.

What You’ll Receive:

• The competitive base pay for this position ranges from ($225000 - $325000). This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors including the candidate’s experience qualifications and location.

• Meaningful equity in a fast-growing company- everyone on the team receives stock options — your impact drives our growth and you share in the upside.

• Generous medical dental & vision plans.

• Flexible PTO- take the time you need to recharge.

• Most roles are remote work first with an inclusive collaborative teams utilizing slack as the main form of internal communication.

• Join a passionate team on the cutting edge of AI infrastructure — where culture learning and ownership are at the heart of how we scale.

• $1200 Home Office & Equipment Stipend- We set you up for success from day one with gear and support to create your ideal workspace.

Runpod is committed to maintaining a workplace free from discrimination and upholding the principles of equality and respect for all individuals. We believe that diversity in all its forms enhances our team. As an equal opportunity employer Runpod is committed to creating an inclusive workforce at every level. We evaluate qualified applicants without regard to race color religion sex sexual orientation gender identity national origin age marital status protected veteran status disability status or any other characteristic protected by law. We welcome every qualified candidate eligible to work in the United States; however we are currently unable to sponsor employment visas.

What We Do

Runpod is pioneering the future of AI and machine learning offering cutting-edge cloud infrastructure for full-stack AI applications. Founded in 2022 we are a rapidly growing well-funded company with a remote-first organization spread globally. Our mission is to empower innovators and enterprises to unlock AI's true potential driving technology and transforming industries. Join us as we shape the future of AI. We are building Cloud services focused on accelerating AI adoption. Whether you're an experienced ML developer training a large language model or an enthusiast tinkering with stable diffusion we strive to make GPU compute as seamless and affordable as possible.

Why Work With Us

Our Guiding Virtues Give a sh*t - We want to work with people who care - about our customers and about each other. Look in the mirror - We deeply reflect on our own actions and seek to better ourselves. Courage over comfort - We tackle hard truths and tough situations directly even when it makes us uncomfortable.

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