Network Engineer

About the role

About us

Gimlet is building the first multi-silicon neocloud designed for fast, efficient AI inference.

We combine large-scale compute infrastructure with an execution platform that partitions AI workloads and maps each stage to the hardware best suited to run it.

We work with foundation labs, hyperscalers, and AI-native companies, giving our team access to technical problems spanning frontier models, production infrastructure, and emerging hardware.

About the role

As a Network Engineer, you will build the network infrastructure connecting Gimlet’s compute, storage, and distributed systems. Your work will shape how our data centers are designed, deployed, and operated as the platform scales.

You will work across network architecture, physical infrastructure, provisioning, deployment, and production operations. You will design high-performance network fabrics, bring new sites and hardware online, automate operational workflows, and troubleshoot performance and reliability issues across network and systems boundaries.

What success looks like

In the first 12-18 months, you will:

- Design and deploy network infrastructure for new data centers and hardware expansions

- Improve network performance and reliability for distributed AI workloads

- Automate provisioning, configuration, validation, and monitoring workflows

- Establish repeatable network standards that make infrastructure deployments faster and more reliable

- Troubleshoot complex issues across network, hardware, and distributed systems boundaries

You may be a good fit if you have

- Experience designing, deploying, and operating production data center networks

- Strong fundamentals in routing, switching, performance, and reliability

- Experience with BGP, ECMP, EVPN, VXLAN, and spine-leaf or Clos fabrics

- Knowledge of high-performance networking technologies such as RDMA, RoCE, InfiniBand, or lossless Ethernet

- The ability to troubleshoot across network, hardware, software, and distributed systems boundaries

- Experience automating network infrastructure with Python, Ansible, Terraform, or similar tools

Strong candidates may also have

- Experience with AI/HPC, GPU, or large-scale distributed infrastructure.

- Knowledge of AI application traffic patterns, including collective operations and workload colocation strategies that optimize network performance.

- Experience with cloud networking on GCP, AWS, Azure, or similar platforms.

- Experience with Arista, Cisco, Juniper, or NVIDIA networking platforms, as well as Palo Alto Networks PAN-OS.

- Experience with network automation using Python, Ansible, Terraform, or similar tooling.

- Familiarity with RDMA, RoCE, InfiniBand, or other high-performance networking environments.