Senior AI Hardware Systems Architect - Remote

Blaze Talent; San Francisco (CA); Remote; USD 180,000 - 250,000; Full time

Job summary

Neo Cloud is seeking a Principal Hardware Systems Engineer to design, deploy, and manage AI hardware at scale. You will bridge customer needs, system architecture, and production operations to define hardware for demanding AI/ML workloads.

You will lead architecture decisions, engage with vendors, and mentor senior engineers while ensuring secure, reliable, and cost-efficient hardware operation across all layers from design to deprecation.

Qualifications

• 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.

Responsibilities

• Identify customer requirements and translate them into scalable hardware architectures.
• Engage with customers, solutions architects, and product teams to forecast future AI hardware needs.
• Design, deploy, and operate AI cloud hardware at scale.
• Architect and deploy NVIDIA GPU infrastructure (Blackwell, GB200, GB300, NVL rack-scale).
• Design rack-scale infra with NVLink/NVSwitch, InfiniBand or Spectrum-X RoCE, power, cooling, and cabling.

Skills

Hardware engineering

AI hardware

System architecture

Incident response

Vendor management

Mentorship

Distributed systems

Tools

NVIDIA GPUs

NVLink

NVSwitch

Infiniband

Spectrum-X

ConnectX

Job description

Neo Cloud is seeking a Principal Hardware Systems Engineer to design, deploy, and manage AI hardware at scale. You will bridge customer needs, system architecture, and production operations to define hardware for demanding AI/ML workloads.

You will lead architecture decisions, engage with vendors, and mentor senior engineers while ensuring secure, reliable, and cost-efficient hardware operation across all layers from design to deprecation.