Network Engineer (AI)

Location: San Francisco, United States

Cash compensation: $150,000–$300,000 per year plus equity incentives.

Company

hirify.global is building an open superintelligence stack that provides AI teams with compute, environments, evaluations, secure sandboxes, high-performance training, and deployment infrastructure.

What you will do

• Design and deploy scalable datacenter network topologies for GPU training, inference, storage, and management traffic.
• Configure and operate high-performance Ethernet/RoCE and InfiniBand fabrics, including routing, redundancy, and capacity standards.
• Automate network provisioning, configuration validation, upgrades, and rollback procedures.
• Diagnose packet loss, congestion, link failures, and distributed collective communication performance across hosts and switches.
• Benchmark network performance with infrastructure and ML teams and translate workload needs into measurable acceptance criteria.
• Build monitoring for port health, errors, utilization, congestion, and fabric topology while improving incident response runbooks.

Requirements

• 3+ years of production datacenter networking experience.
• Strong knowledge of Ethernet, TCP/IP, routing, switching, and redundant network design.
• Hands-on experience with high-performance GPU networking using InfiniBand or RoCE.
• Experience troubleshooting Linux hosts, NICs, switches, and physical links.
• Ability to automate network operations with Python, Ansible, or comparable tools.
• Knowledge of leaf-spine architectures, BGP, ECMP, VLANs, network segmentation, RDMA, congestion control, telemetry, and link diagnostics.

Nice to have

• Experience operating 400G/800G networks or large multi-rack GPU clusters.
• NVIDIA Spectrum or Quantum networking experience.
• NCCL performance analysis and distributed training troubleshooting.
• Experience with EVPN/VXLAN, SONiC, network source-of-truth systems, simulation, automated validation, or capacity planning.

Culture & Benefits

• Work directly with AI customers, from startups training foundation models to enterprises deploying large-scale inference infrastructure.
• Collaborate with engineering, infrastructure, ML, datacenter operations, and hardware vendors.
• Contribute to open frontier AI and infrastructure intended to democratize access to large-scale computing.
• Cash compensation of $150,000–$300,000 plus equity incentives.