Network Engineer (AI)

TL;DR

Network Engineer (AI): Building and scaling networking infrastructure that powers AI research and deployment with an accent on physical network builds, software-defined networking, and automation systems. Focus on configuring routers, writing automation, troubleshooting physical connectivity, and designing scalable network architectures.

Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY. Expect all staff to be in one of our offices at least 25% of the time.

Salary: $320,000 - $405,000 USD

Company

hirify.global is an AI safety company working to build reliable, interpretable, and steerable AI systems.

What you will do

• Design, deploy, and maintain high-performance networks across multiple data center sites, including managing physical infrastructure, routing protocols, and network security.
• Develop software to automate network provisioning, configuration management, and operational workflows.
• Implement comprehensive monitoring, build debugging tools, investigate outages, and drive continuous reliability improvements.
• Plan and execute network expansions to new sites and facilities, including working with vendors, managing physical builds, and migrating live traffic.
• Partner with compute, storage, and ML infrastructure teams to optimize network performance for AI workloads and troubleshoot complex distributed systems issues.
• Participate in on-call rotation and lead response to network-related incidents.

Requirements

• 5+ years of experience in network engineering, with hands-on experience building and operating production networks.
• Strong software development skills (Python, Go, or similar) and experience building network automation, tooling, or infrastructure software.
• Deep understanding of networking fundamentals: TCP/IP, BGP, ISIS, OSPF, VLANs, VPCs, routing, switching, and network security.
• Experience with the full stack of networking—from physical layer concerns (cabling, optics, hardware) through software-defined networking.
• Comfort working with Linux, command-line tools, and infrastructure-as-code approaches.
• Track record of debugging complex distributed systems issues that span network, compute, and application layers.

Nice to have

• Experience scaling networks in cloud environments (AWS, GCP, Azure) and/or on-premises data centers.
• Background in DevOps/SRE practices including monitoring, observability, and reliability engineering.
• Experience with Kubernetes networking, container orchestration, or service mesh technologies.
• Prior work at startups, small ISPs, or environments requiring broad technical responsibilities.
• Familiarity with AI/ML infrastructure and the unique networking requirements of large-scale training clusters.

Culture & Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Lovely office space in which to collaborate with colleagues.

Hiring process

• We encourage you to apply even if you do not believe you meet every single qualification.
• We think AI systems like the ones we're building have enormous social and ethical implications.
• We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.