CPU Storage Tech Lead (AI Infrastructure)

TL;DR

CPU Storage Tech Lead (AI Infrastructure): Defining and driving the server compute and storage architecture strategy for Stargate infrastructure with an accent on CPU platforms, memory configurations, and disaggregated storage systems. Focus on optimizing compute and storage systems for training, inference, and scaling large-scale AI clusters.

Location: Must be based in San Francisco or Seattle

Salary: $342,000 – $555,000 + Equity

Company

hirify.global is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

What you will do

• Own the technical strategy for CPU and storage compute infrastructure across current and future generations.
• Evaluate CPU platforms based on performance, efficiency, memory bandwidth, PCIe topology, and cost.
• Define storage architectures for AI environments, including local NVMe, shared storage, caching tiers, and high-performance data pipelines.
• Drive server platform decisions integrating CPU, memory, NIC, GPU, and storage subsystems.
• Partner with silicon vendors (AMD, Intel, ARM) and OEMs to influence roadmaps, feature requests, and qualification plans.
• Lead bring-up and validation efforts for new CPU and storage platforms in lab and production environments.

Requirements

• Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
• 10+ years of experience in server hardware, systems architecture, or hyperscale compute platforms.
• Deep expertise in modern CPU architectures (x86, ARM) and server platform design.
• Strong understanding of memory systems, PCIe/CXL fabrics, and NUMA behavior.
• Experience with storage systems including NVMe, SSD qualification, and distributed storage.
• Must be based in San Francisco or Seattle.

Nice to have

• Experience designing infrastructure for large-scale AI or HPC environments.
• Familiarity with CPU vendor roadmaps across AMD, Intel, and ARM ecosystems.
• Experience with distributed storage architectures supporting GPU clusters.
• Knowledge of fleet operations, hardware lifecycle management, and production deployments at scale.

Culture & Benefits

• Opportunity to build the physical infrastructure powering next-generation large-scale AI systems.
• Highly strategic role influencing long-range infrastructure decisions at a global scale.
• Competitive compensation package including base salary and equity.
• Collaboration with top-tier silicon vendors and cross-functional hardware engineering teams.