Senior Systems Engineer (AI)

TL;DR

Senior Systems Engineer (AI): Leading the hands-on bringup and deployment of GPU clusters for large-scale AI training with an accent on rack integration, network fabric validation, and performance tuning. Focus on building repeatable deployment systems and optimizing GPU infrastructure for production readiness.

Location: Must be based in Seattle, US

Company

hirify.global is a startup building next-generation AI infrastructure, delivering highly performant and scalable GPU clusters purpose-built for large-scale AI training and inference.

What you will do

• Execute end-to-end bringup of GPU nodes and racks, from physical installation to production readiness.
• Configure and validate high-speed network fabrics including InfiniBand and RoCE.
• Perform GPU-to-GPU and node-to-node performance validation using NCCL and RDMA.
• Troubleshoot hardware, firmware, and fabric-level issues to ensure stability.
• Contribute to automation efforts for provisioning and cluster validation processes.
• Collaborate with networking, systems software, and data center teams to support rapid scaling.

Requirements

• 5–8+ years of experience in infrastructure engineering, hardware deployment, or data center operations.
• Hands-on experience deploying GPU servers such as HGX or DGX platforms.
• Proficiency with high-speed networking including InfiniBand, RoCE, and Ethernet fabrics.
• Strong Linux systems knowledge and experience troubleshooting distributed systems.
• Must be comfortable working onsite in data center environments as needed.

Nice to have

• Experience in AI/ML infrastructure or HPC environments.
• Familiarity with CUDA and performance tuning tools.
• Automation proficiency using Python, Ansible, Terraform, or Bash.
• Experience working in high-density power and cooling environments.

Culture & Benefits

• Fast-paced startup environment with an emphasis on ownership and bias for action.
• Opportunity to build foundational infrastructure for frontier AI workloads.
• Direct impact on scaling AI capabilities through hands-on technical contribution.