Staff Network Engineer

Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.

We’re seeking a Staff Network Engineer (L6/L7) focused on designing, scaling, and optimizing large-scale RoCEv2 data center networks powering next-generation AI and ML infrastructure.

You’ll work closely with network architects and infrastructure leadership to execute network designs and ensure operational stability as we scale cluster sizes to over 100,000 GPUs. You will drive multi-team technical direction, influence cross-functional outcomes, and own critical components of network performance and reliability. You’ll remain hands-on with high-speed optics, switching, routing, and congestion management in production clusters, while developing the standards and automation tooling that other engineers build and operate against.

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  Set multi-team technical direction and influence cross-functional network architecture decisions to ensure seamless infrastructure scaling.

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  Design, deploy, and optimize large-scale RoCEv2 data center networks supporting AI and ML clusters from thousands to 100,000+ GPUs.

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  Implement and tune congestion management protocols across RDMA fabrics, including PFC, ECN, and DCQCN, based on real production telemetry.

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  Build and standardize automation, validation, and observability patterns that prevent misconfiguration and reduce manual operational overhead.

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  Serve as a senior technical escalation point for complex network failures and actively mentor mid-level engineers in advanced troubleshooting and design.

• Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.

• Extensive experience deploying and operating RDMA and RoCEv2 networks in large-scale production environments supporting AI or HPC workloads.

• Advanced knowledge of switching hardware and NOS, such as Arista, Juniper, and custom solutions using SONiC, including high-speed Ethernet fabrics.

• Proven hands-on experience with congestion management and performance tuning using PFC, ECN, and DCQCN.

• Strong experience with high-speed optics and cabling including 400G, 800G, AEC, AOC, DAC, and structured cabling at scale.

• Strong automation mindset, with experience using Python, Ansible, Terraform, Git, and production observability tooling.

• Demonstrated ability to autonomously solve complex, novel problems and translate broad architectural goals into executable project plans.

TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.

TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.

All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.

Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.

By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.