Who We Are

Join us in putting the world’s compute behind the people building what comes next.

At Hyperbolic, we’re making global AI compute liquid. We bring fragmented, heterogeneous GPU capacity together into one unified, productive platform, making it easier to access, sell, resell, manage, and orchestrate the resources that power AI. For neocloud, we turn GPU capacity into productive infrastructure that delivers lasting value and accelerate their time to market.

We believe bold ideas deserve the computing power to become reality. We’re building toward a future where compute flows as freely as electricity, available when and where it’s needed, so builders everywhere can turn their most ambitious ideas into breakthroughs.

We’re looking for curious, driven people who take ownership, challenge assumptions, and care deeply about what they build. If you’re energized by hard problems and want to help shape how the world accesses AI, we’d love to build with you.

About the Role

We are seeking a highly technical Vice President of Infrastructure to build and scale the foundational infrastructure powering our AI cloud platform.

This is a hands-on executive leadership role. While you will own infrastructure strategy, organizational growth, and executive-level decision making, we expect you to remain deeply engaged in architecture, design, and engineering execution. You should expect to spend approximately 30-40% of your time directly contributing to technical design, architecture reviews, debugging critical production issues, and partnering with engineers on implementation.

The ideal candidate has previously built and scaled cloud platforms, preferably GPU-native cloud infrastructure supporting AI training and inference workloads. You have experience operating at the intersection of executive leadership and hands-on engineering and are excited to help build both the technology and the team.

What You'll Own

Cloud Infrastructure Architecture

Lead the design and evolution of our AI cloud platform

Define the architecture for GPU orchestration, compute scheduling, networking, storage, and distributed systems

Make critical decisions regarding cloud infrastructure, bare-metal deployments, and platform scalability

Personally participate in architecture reviews and key technical initiatives

GPU Cloud Platform

Build and scale large GPU clusters supporting customer workloads

Design systems for GPU provisioning, scheduling, utilization optimization, and capacity management

Drive platform reliability and performance for AI training and inference workloads

Partner closely with engineering teams on infrastructure requirements for next-generation AI systems

Technical Leadership

Remain deeply involved in engineering decisions and technical direction

Contribute directly to infrastructure design and implementation efforts

Review architecture proposals, system designs, and major infrastructure changes

Act as the technical escalation point for complex infrastructure challenges

Infrastructure & Reliability

Establish best practices for Kubernetes, observability, CI/CD, security, and operational excellence

Build SRE and Platform Engineering functions from the ground up

Define reliability standards including SLOs, SLIs, incident response processes, and capacity planning

Drive automation across infrastructure operations

Organizational Leadership

Recruit and develop world-class Infrastructure, Platform, and SRE teams

Build a high-performance engineering culture focused on ownership and execution

Partner with executive leadership on company strategy and infrastructure investments

Manage infrastructure budgets, vendor relationships, and capacity planning

Required Experience

Must-Have Background

12+ years building and operating large-scale infrastructure systems

Experience leading infrastructure organizations while remaining hands-on technically

Previous experience building or operating a cloud platform at scale

Experience building GPU infrastructure or AI/ML compute platforms

Proven track record scaling infrastructure in high-growth startup environments