Senior WAN Network Engineer

Posted 14 Hours Ago
Be an Early Applicant
2 Locations
In-Office or Remote
Senior level
Artificial Intelligence • Hardware • Software • Semiconductor
The Role
Design, deploy, and maintain global WAN connectivity across leased lines and dark fiber. Collaborate with carriers, configure and troubleshoot routing and security (BGP, IPSec, MACsec, VXLAN/EVPN), implement redundancy/QoS, monitor performance, support cloud connectivity (AWS/Azure/GCP), provide Tier 3 incident response, and automate network configuration with Python, Ansible, or Terraform.
Summary Generated by Built In

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About The Role

We are seeking a highly skilled WAN Network Engineer to design, implement, manage, and optimize global connectivity. The ideal candidate will have strong experience with carrier networks, routing protocols, and network security, and will play a critical role in ensuring high availability, performance, and reliability of global network services.

Responsibilities

  • Design, deploy, and maintain WAN network across leased lines and dark fiber for low latency and 99.999% availability. 

  • Collaborate with telecom providers and ISPs for circuit provisioning, upgrades, and issue resolution.

  • Configure, troubleshoot, and optimize security and routing protocols (IPSec Tunnels, MACsec, BGP, VXLAN, EVPN). 

  • Monitor WAN performance, latency, packet loss, capacity utilization.  Analyze traffic patterns to predict growth and trigger circuit upgrades or hardware refreshes before bottlenecks occur.

  • Implement redundancy, failover, QoS, and traffic engineering to ensure business continuity.

  • Participate in network modernization and cloud connectivity projects (AWS, Azure, GCP).

  • Provide Tier 3 support for WAN-related incidents and root cause analysis.

  • Develop and maintain network documentation, diagrams, and standard operating procedures.

  • Use Python, Ansible, or Terraform to deploy configurations and manage network state at scale.

  • Support network security initiatives including site-to-site VPNs and perimeter connectivity. Ensure compliance with security, governance, and operational best practices.

Requirements

  • Bachelor’s degree in Computer Science, Electrical Engineering, or Computer Engineering. Master’s degree is preferred. 

  • 6+ years of experience in WAN network engineering, or Service Provider network, or Hyper-scale Data Center environment.

  • Industry certifications such as, CCIE or JNCIE.  Strong knowledge of BGP routing protocols and WAN technologies.

  • Experience with major network vendors such as Arista, Cisco, Juniper, or Palo Alto.

  • Strong troubleshooting and analytical skills, and excellent communication and documentation skills.

  • Experience with cloud networking and hybrid network architectures.

  • Expertise with network automation tools (Python, Ansible, Terraform).

  • Knowledge of network monitoring tools (SolarWinds, Kentik, ThousandEyes, or similar).

  • Ability to participate in on-call rotation and after-hours maintenance.

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Skills Required

  • Bachelor's degree in Computer Science, Electrical Engineering, or Computer Engineering
  • Master's degree
  • 6+ years of WAN network engineering or service provider/hyperscale data center experience
  • Industry certifications such as CCIE or JNCIE
  • Strong knowledge of BGP and WAN technologies
  • Experience with Arista, Cisco, Juniper, or Palo Alto
  • Experience with cloud networking and hybrid network architectures (AWS, Azure, GCP)
  • Expertise with network automation tools: Python, Ansible, Terraform
  • Knowledge of network monitoring tools (SolarWinds, Kentik, ThousandEyes, or similar)
  • Ability to participate in on-call rotation and after-hours maintenance
  • Strong troubleshooting, analytical, communication, and documentation skills
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The Company
774 Employees
Year Founded: 2015

What We Do

Cerebras Systems develops wafer-scale semiconductor hardware, AI supercomputers, and software/cloud services for training and inference. Its CS-2 and CS-3 systems help organizations build on-premise AI supercomputers, while pay-as-you-go cloud offerings provide developers and enterprises access to its computing platform. The company focuses on making AI training and inference faster and easier for diverse research and production workloads at scale worldwide.

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