Network Engineer

Gimlet Labs Inc.
San Francisco, CA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Border Gateway Protocol Common Lisp Object Systems Cloud Computing Data Centers Distributed Systems Ethernet InfiniBand Python (Programming Language) Network Architecture
+19 more
Network Connections Network Planning and Design Routing Network Administration Operational Databases Performance Tuning Remote Direct Memory Access Ansible Computer Networking Systems Google Cloud Computer Network Operations Computer Network Technologies Juniper Deployment Automation Palo Alto Networks Terraform Open Network Automation Platform Cisco Network Optimization

Job description

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

Requirements

Network Architecture/Engineering, Artificial Intelligence (AI), Network Architecture/Engineering, Network Administration/Management, Network Operations Center, Distributed Computing, Network Connectivity, Identify Issues, Network Systems, Network Design, * 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.

Benefits & conditions

Gimlet is expanding from its core technology into a production neocloud spanning new hardware, customers, and data centers.

  • Solve hard problems.
  • Own meaningful work.
  • Build for production.
  • Help define what’s next.

Agency Policy:Gimlet Labs does not accept unsolicited resumes from recruitment agencies or search firms. Any unsolicited resumes submitted without a signed agreement will be considered the property of Gimlet Labs, and no fees will be paid.

About the company

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.

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