About the Role
xAI is building at a furious pace with the latest hardware to help people understand the universe. We are in need of a Network Deployment Engineer that has spent the last 8 years automating away human cycles required to build and maintain hyper scale production networks that reside in data centers.
You will own xAI’s network deployment speed and accuracy, creating automation, workflows and dashboards leveraging our modelling, source of truth and provisioning software systems. Your tools will be used by the team and technicians to build tens of thousands of devices and millions of links for our different data center and backbone topologies. Then, your tooling will keep the network perpetually consistent for configuration and operating system versions, from simple deploy and forget to complex sequencing for topology changes. You will help us remove tens of thousands of repetitive human cycles a year and keep our team small and nimble.
Responsibilities Will Include
- Liaise with engineers from different teams to build strategies and roadmaps that will address short term needs while ensuring a long term vision is met.
- Use python to create an ecosystem of tools and dashboards that onsite technicians can use to build our network products and maintain it with minimal human cycles.
Required Qualifications
- 8+ years of experience in using python to automate hyper scale networks.
- 10+ years in the networking industry.
- 3+ years in a team lead role.
- Understanding of networking topologies, protocols and best practices (e.g., BGP, OSPF, ROCEv2 etc.).
Preferred Experiences
- Experience in AI/ML infrastructure or large-scale GPU clusters.
- Strong problem-solving skills and ability to thrive in a fast-paced, ambiguous setting.
Location
Work will be in-office based out of either Palo Alto, California, Dublin, Ireland or Seattle, Washington. There will be significant travel expected to data center buildouts. For Dublin and Seattle based employees, additional travel to our head office in Palo Alto will be required for team collaboration. Travel to Memphis may account for up to 25-30% of time during peak buildout phases.
