Senior Network Engineer

About the Role

Together AI is looking for a Senior Network Engineer to design, deploy, and operate the global network infrastructure supporting our production services and high-performance AI compute environments.

This is a hands-on engineering role for someone with deep networking expertise who can also troubleshoot across Linux, Kubernetes, automation, and application boundaries. You will work on large-scale, multi-vendor data center networks and help ensure they remain highly available, reliable, scalable, and performant.

The ideal candidate has strong networking fundamentals, experience operating complex networks at scale, and a structured, evidence-based approach to troubleshooting. You should be comfortable owning problems from initial investigation through root cause and resolution, including situations where the issue may extend beyond the network itself.

Requirements

8+ years of professional experience designing, building, and supporting large-scale production data center, cloud, service-provider, or high-performance computing networks (excluding enterprise networks).

Deep understanding of TCP/IP and strong experience with technologies such as BGP, OSPF, VXLAN, EVPN, ECMP, and QoS.

Experience designing and supporting multi-tenant network environments using technologies such as VRFs, VLANs, overlays, and policy-based segmentation.

Hands-on experience deploying and troubleshooting network platforms from vendors such as Arista, Cisco, Juniper, and NVIDIA.

Strong troubleshooting skills using tools such as Wireshark, tcpdump, MTR, curl, nmap, and standard Linux networking utilities.

Ability to diagnose connectivity, latency, packet-loss, routing, and performance issues across the network, host, and application layers.

Experience developing or maintaining network automation using Python, Ansible, or similar tools.

Experience working through a Git-based software development lifecycle, including branching, code review, validation, linting, testing, CI/CD, deployment, and rollback.

Working knowledge of Kubernetes networking, including pods, services, CNIs, and basic connectivity troubleshooting.

Foundational knowledge of RDMA networking and technologies such as RoCE or InfiniBand.

Experience with cloud networking in AWS, GCP, or Azure.

Strong Linux administration and troubleshooting skills.

Responsibilities

Design, deploy, operate, and maintain global, multi-vendor, multi-protocol networks supporting high-performance AI compute infrastructure.

Troubleshoot complex network and application-connectivity issues, identify root causes, and drive problems through resolution.

Analyze telemetry, packet captures, logs, and performance data to identify network degradation, congestion, packet loss, and capacity constraints.

Participate in architecture and design reviews to ensure solutions meet requirements for performance, availability, scalability, security, and operational supportability.

Develop and maintain automation, validation, and operational tooling that improves network reliability and reduces manual effort.

Evaluate network hardware, software, optics, and emerging technologies for use in production environments.

Establish standards and operational best practices for network design, deployment, monitoring, change management, and incident response.

Lead projects addressing complex technical challenges and contribute directly to the network engineering roadmap.

Partner with infrastructure, systems, security, and application teams to troubleshoot issues that cross traditional ownership boundaries.

Preferred

Hands-on experience deploying or operating RoCE and/or InfiniBand fabrics.

Experience supporting GPU clusters, HPC environments, distributed storage, or other high-bandwidth and latency-sensitive workloads.

Understanding of AI training and inference traffic patterns and the demands they place on network infrastructure.

Experience operating networks spanning thousa …