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Senior Network Automation Engineer

TensorWave · TensorWave is an AMD-exclusive cloud platform that leverages AMD Instinct GPUs and ROCm for high-performance AI workloads.

Las Vegas, NevadaEngineering101-250 employeesPosted 10 days ago
Series B · $350Mraised 5 months agoled by Western Frontier, Nexus Venture Partners, AMD

This board only lists companies whose most recent round closed in the last 180 days.

Apply on TensorWave’s site

About TensorWave

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.

About the Role

We’re looking for Network Automation Engineers to join our team during an exciting phase of growth. In this role, you’ll be responsible for designing and building scalable automation systems for deploying, managing, and operating large-scale AI network fabrics, working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.

What You’ll Do

  • Design automation for network deployment and lifecycle management

  • Build validation, testing, and reconciliation workflows

  • Develop CI/CD pipelines for network changes

  • Support large-scale Ethernet fabric growth

  • Provide automated configuration and firmware management support for networking gear

  • Integrate NetBox as a source of truth

Who You Are

Basic Qualifications

  • Bachelor of Science in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience

  • 5+ years of networking automation, or similar engineering experience

  • Demonstrated expertise in Python, Java, Go, or Rust

  • Expertise in Automation and related tooling - Ansible, NetBox

  • Experience with CI/CD pipelines and Git-based workflows

  • Multi-Vendor Experience - Juniper, Cisco, Arista, Whitebox

  • NOS Experience - Junos, IOS/IOS-XE, NX-OS, EOS, SONiC

Preferred Qualifications

  • 100G+ environments

  • AI, GPU, or HPC exposure

  • Experience with automated Cabling validations and Zero Touch Provisioning

  • Experience with scale-up and scale-out architectures

  • Experience managing very large Ethernet fabrics

  • Experience with large edge and ingress networks

    What We Offer

  • Stock Options

  • 100% paid Medical, Dental, and Vision insurance for Employees

  • Company Health Savings Account Contributions

  • 100% paid Short Term and Long Term Disability Insurance for Employees

  • Life and Voluntary Supplemental Insurance Options

  • Other Insurance Options, such as Pet & Legal Insurance

  • Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support

  • Flexible Spending Account

  • 401(k)

  • Employee Assistance Program

  • Flexible PTO

  • Paid Holidays

  • Parental Leave

  • Other In-Office Perks

 

Equal Employment Opportunity

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.

 

Reasonable Accommodations

TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact [email protected].

 

Employment Eligibility

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

 

Background Checks

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

 

Data Privacy Notice

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.

Apply on TensorWave’s site

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