Computer Systems Architect; AI & GPU Server Platforms

About the Role

ZT Systems is seeking a Principal Compute Systems Architect to lead the design, integration, and validation of next-generation AI and machine learning server platforms. This role owns system-level architecture across CPU, GPU, memory, and high-speed interconnects, driving platforms from early concept through high-volume production.

This position is ideal for senior engineers from Intel, AMD, NVIDIA, or hyperscale cloud environments who have delivered complex compute platforms used at scale.

• Own system-level architecture for AI and ML server platforms integrating CPUs, GPUs, high-speed memory (DDR5, HBM), and PCIe fabrics
• Define platform requirements, specifications, and architectural trade-offs from early concept through production launch
• Drive CPU–GPU topology, memory hierarchy, and IO expansion strategies for high-density compute systems
• Lead cross-functional collaboration with electrical, mechanical, thermal, firmware, silicon, manufacturing, and supply-chain teams
• Guide board-level implementations including server baseboards, GPU carrier boards, IO backplanes, and add-in cards
• Lead system bring-up, validation, and debug across pre-silicon, emulation, post-silicon, and production hardware
• Specify validation strategies, production test methods, and quality limits for high-volume manufacturing
• Partner with silicon vendors and suppliers to qualify components, materials, and technologies
• Mentor senior and junior engineers and provide technical leadership across multiple programs

• Bachelor’s degree in Electrical Engineering, Computer Engineering, or related field
• 12+ years of experience designing, integrating, or validating server or compute platforms
• Deep understanding of CPU and GPU-based systems and accelerator architectures
• Strong experience with high-speed interfaces (PCIe Gen4/Gen5, DDR4/DDR5, SAS/SATA, USB)
• Knowledge of power delivery networks, signal integrity, and high-speed PCB design principles
• Experience with system bring-up, debug, and validation of complex multiprocessor systems
• Ability to drive architectural decisions balancing performance, cost, power, reliability, and schedule
• Strong technical communication and leadership skills

• Experience with AI training or inference platforms
• Familiarity with HBM, accelerator fabrics, or coherent interconnects
• Background in hyperscale or cloud infrastructure environments