Vice President, GPUaaS and Token Factory

Location: Silicon Valley, CA (Hybrid, 4 days onsite)
Reports To: Chief Technology Officer

About Our Client

Our client is building next generation AI infrastructure with significant power capacity, data center expertise, and hyperscale AI compute capabilities. The company is expanding its AI platform business by launching a GPU-as-a-Service (GPUaaS) and Token Factory platform that leverages existing AI infrastructure while integrating distributed GPU capacity across multiple marketplaces. Their platform is designed to provide AI workbench services, model hosting, Kubernetes hosting, inference services, and private AI cloud solutions. By combining owned infrastructure with advanced AI services, the company is creating a scalable platform that delivers high performance AI computing solutions for developers and enterprises.

Position Overview

Our client is seeking a Vice President, GPUaaS & Token Factory to lead the strategy, architecture, development, and commercialization of its GPU-as-a-Service platform and Token Factory. This executive will drive the complete platform lifecycle, from designing the GPU infrastructure and inference platform to launching and scaling the business. The ideal candidate will combine deep AI infrastructure expertise with strong leadership and commercial experience, helping transform cutting edge GPU infrastructure into a revenue generating AI platform. This is a unique opportunity to build a 0-to-1 AI platform while leading a high performing engineering organization and working directly with executive leadership.

Responsibilities

Platform Architecture

• Lead the architecture and development of the GPUaaS platform, including compute rental and control plane capabilities.
• Design and build the Token Factory inference layer utilizing technologies such as vLLM and OpenAI-compatible APIs.
• Develop an open-weight AI model marketplace and storefront.
• Define scalable platform architecture supporting enterprise AI workloads.

Engineering Leadership

• Build, hire, and lead a world-class engineering organization.
• Manage teams specializing in:
  • AI Engineering
  • MLOps
  • Kubernetes
  • GPU Clusters
  • AI Infrastructure
  • GPU Networking
  • DCIM
• Collaborate with external implementation partners to accelerate delivery.

Product & Platform Execution

• Execute the platform roadmap from:
  • Bare Metal GPU Infrastructure
  • Managed Kubernetes
  • AI Workbench
  • AI Inference Services
  • Private AI Cloud
• Deliver projects within timeline and budget.
• Drive key platform performance metrics including revenue per megawatt and platform adoption.

Commercial Strategy

• Support go-to-market initiatives targeting:
  • AI startups
  • Developer communities
  • Enterprise customers
• Build monetization strategies around GPU, platform, and inference services.
• Optimize token-based and inference-based pricing models.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's preferred).
• 8+ years of experience in cloud-native and AI-native technologies.
• Recent experience within high-growth AI startups or scale-up organizations.
• Proven success building AI services on GPU bare metal and cloud infrastructure.

Qualifications

• Strong knowledge of:
  • Kubernetes
  • Slurm
  • vLLM
  • Triton Inference Server
  • GPU Scheduling
  • AI Infrastructure
  • DCIM
• Experience with managed Kubernetes platforms such as Run:AI, OpenShift AI, or similar.
• Strong understanding of token-based pricing models and AI infrastructure economics.
• Previous experience working for:
  • GPU Cloud Providers
  • Neocloud Providers
  • AI Infrastructure Software Companies
  • AI Platform Organizations

Preferred Skills

• AI Infrastructure Architecture
• GPU Cloud Platforms
• LLM Deployment
• AI Inference Optimization
• Cloud Native Technologies
• Platform Engineering
• Distributed Systems
• MLOps
• Infrastructure Scaling
• Executive Leadership
• Product Strategy
• Revenue Growth

Why Join

This opportunity offers the chance to lead the development of a next-generation AI platform built on a unique foundation of owned infrastructure, power capacity, and large-scale data center expertise. The successful candidate will play a pivotal executive role in defining the company's AI platform strategy while building one of the industry's most innovative GPU-as-a-Service and AI inference platforms.