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 thousands of devices, multiple data centers, and multiple geographic regions.
- Familiarity with AI-assisted engineering tools and the ability to validate, test, and safely deploy AI-generated automation or code.
Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.
CompensationWe offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $280,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge.
Equal OpportunityTogether AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.
Please see our privacy policy at https://www.together.ai/privacy
Skills Required
- 8+ years building, managing, and supporting large-scale hybrid data center networks (excluding enterprise networks).
- High proficiency with TCP/IP networking architecture and technologies such as BGP, OSPF, VXLAN, EVPN, and QoS.
- Experience developing network automation pipelines using Python, Ansible, or similar infrastructure automation tools.
- Proficient using Wireshark, tcpdump, nmap, MTR, and curl for diagnosing connectivity, latency, and network bottlenecks.
- Experience designing and supporting multi-tenant networks.
- Hands-on experience deploying and supporting network devices from Cisco, Arista, Juniper, and Mellanox.
- Experience working with cloud networks such as AWS, GCP, and Azure.
- Solid experience working in and troubleshooting within a Linux environment.
- Knowledge of RoCE and Infiniband protocols.
- Experience with Docker, Kubernetes, or Slurm.
- Understanding of AI training workloads and their network demands.
Together AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Together AI and has not been reviewed or approved by Together AI.
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Fair & Transparent Compensation — Pay is considered competitive for the company’s stage, with especially strong offers for technical and research roles. A posted AI researcher range reaching into the high-$200Ks alongside equity and benefits reinforces the overall pay positioning.
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Equity Value & Accessibility — Equity is commonly included alongside base salary, giving employees ownership exposure tied to company growth. Total compensation is often framed around salary plus equity for specialized roles.
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Flexible Benefits — Job listings describe a flexible time‑off policy and hybrid or remote work options. Commuter perks and regular team events are also cited as part of the package.
Together AI Insights
What We Do
Together AI is a research-driven artificial intelligence company. We contribute leading open-source research, models, and datasets to advance the frontier of AI. Our decentralized cloud services empower developers and researchers at organizations of all sizes to train, fine-tune, and deploy generative AI models. We believe open and transparent AI systems will drive innovation and create the best outcomes for society
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