Neo Cloud - Principal Hardware Systems Engineer

Location: San Francisco, Seattle

Department: Data Center

Location Type: HYBRID

Employment Type: FULL_TIME

• Identifying customer requirements
• Engage directly with customers, solutions architects, and product teams to understand future hardware requirements for AI/ML workloads.
• Extrapolate from current usage patterns and industry trends to anticipate future requirements.
• Partner with vendors and drive their roadmaps.

• Design, implement, and operate AI cloud hardware.
• Architect, evaluate, and Deploy NVIDIA GPU infrastructure, including Blackwell-based B200, GB200, GB300, DGX and NVL rack-scale systems.
• Design rack-scale infrastructure encompassing NVLink and NVSwitch fabrics, Infiniband or Spectrum-X Ethernet with RoCE for scale-out networking; power delivery, liquid cooling, cabling and serviceability.
• Take a system-level approach that accounts for the full characteristics of AI workloads, building end-to-end solutions.
• Architect for the specific demands of AI workloads focusing on performance, security, resiliency and cost. 
• Design and implement consistent and efficient hardware operation. 
• Take end-to-end ownership of hardware from design, supply chain planning, deployment, operation and ultimately deprecation. 
• Ensure security and compliance. 
• Strong debugging skills and analytical skills to identify failures across a variety of electrical, thermal, optical, mechanical and software failures. 

• Strong bias to action and resolution of technical decisions. 
• Set technical direction and best practices for the hardware organization; author and review design documents for significant architectural changes.
• Provide deep technical mentorship to senior and staff engineers; raise the engineering bar across the team through code review, design review, and hands-on collaboration.
• Influence technical strategy across adjacent teams.

• 10+ years of professional hardware engineering experience building and operating hardware at massive scale.
• Direct experience with AI-focused hardware deployments across different hardware vendors, including NVIDIA GPU platforms.
• Experience with NVIDIA BLackwell, GB200 or GB300 NVL72.
• Experience with NVLink, NVSwitch, InfiniBand or Spectrum-X Ethernet, ConnectX networking, and BlueField DPUs.
• Deep system level expertise. 
• Proven experience operating large-scale distributed systems in production, including on-call ownership, incident response, and driving systemic reliability improvements.
• Strong systems programming skills.
• Excellent written and verbal communication skills.