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About the Role

Gimlet Labs is seeking a Network Engineering Lead to own the strategy, architecture, design, deployment standards, and operations of the network infrastructure that powers Gimlet's AI datacenters. This person will be responsible for both the front-end network that connects customers, services, sites, and external networks, and the back-end network that enables high-performance AI infrastructure, GPU clusters, storage, control planes, management networks, and data center interconnect. You will define Gimlet's network architecture from first principles, build the roadmap for scaling across multiple sites, establish engineering and operational standards, and lead the team responsible for delivering and operating production-grade network infrastructure. This is a senior technical leadership role for someone who can operate at multiple altitudes: network strategy, architecture, vendor selection, physical deployment standards, routing design, observability, automation, incident response, and team-building.

Responsibilities

Define Gimlet's end-to-end network architecture across data centers, AI clusters, customer-facing services, management networks, and inter-site connectivity.
Own the network roadmap for current and future sites, including capacity planning, topology, scaling strategy, redundancy, performance, and operational readiness.
Lead design for both front-end connectivity and back-end AI infrastructure fabrics.
Establish standards for routing, switching, IP addressing, cabling, optics, out-of-band management, observability, change management, and network acceptance.
Partner with Data Center Operations, Deployment TPMs, Network Capacity Delivery, Site Operations, Facilities, Supply Chain, and Engineering to bring new capacity online.
Build repeatable network deployment and validation processes for new sites and expansions.
Own network operations, including monitoring, incident response, troubleshooting, postmortems, vendor escalation, and reliability improvements.
Create the hiring and team plan for Network Engineering, including network deployment engineers, capacity delivery, and future operations roles.
Develop automation and tooling strategy for configuration management, validation, telemetry, and fleet-scale network operations.
Serve as Gimlet's technical authority on network architecture, network vendor decisions, and production network readiness.

Requirements

Deep experience designing and operating large-scale data center networks, cloud networks, AI infrastructure networks, HPC networks, or hyperscale network environments.
Understand both external/front-end networking and internal/back-end data center fabrics.
Hands-on experience with routing, switching, BGP, EVPN/VXLAN, spine-leaf fabrics, WAN/DCI, out-of-band management, optics, structured cabling, and network telemetry.
Ability to design networks for high availability, high throughput, low latency, operational simplicity, and rapid deployment.
Experience operating production networks where uptime, performance, and change discipline matter.
Comfortable making build-vs-buy decisions, evaluating network vendors, and setting technical standards.
Ability to partner with deployment, facilities, supply chain, and site teams to turn network designs into working infrastructure.
Excited to build a team and operating model, not just design architecture on paper.
Communicate clearly with executives, engineers, vendors, deployment teams, and data center operators.

Skills

BGP
EVPN/VXLAN
Spine-leaf fabrics
WAN/DCI
Out-of-band management
Optics
Structured cabling
Network telemetry
Python
Go
Ansible
Terraform
NetBox
GitOps workflows
NVIDIA networking
High-performance Ethernet fabrics
Storage networking
Cluster interconnects
Data center interconnect architectures
InfiniBand
RoCE
RDMA
High-density compute
HPC
Distributed training environments
Network automation
Monitoring systems
Telemetry systems
Network health monitoring
Latency monitoring
Congestion monitoring
Packet loss monitoring
Interface error monitoring
Capacity forecasting
Incident response
Root cause analysis
Operational improvement programs

Location

Datacenters

Work Type

Full-time

Experience Level

Senior technical leadership
Early member of the team

About the Company

Gimlet is building the first multi-silicon neocloud designed for fast, efficient inference.
As AI workloads become more complex and new hardware architectures emerge, simply deploying more GPUs isn't enough. The challenge is making increasingly diverse compute work together.
Gimlet's platform intelligently partitions and routes workloads across heterogeneous hardware, enabling step-function improvements in performance and efficiency. Customers deploy through production-grade APIs without needing to think about hardware selection, placement, or optimization.
We work with foundation labs, hyperscalers, and AI-native companies to power production workloads at massive scale and help define the infrastructure layer for the future of AI.
Gimlet is at the very beginning of its journey, and that's what makes this moment special. Most AI infrastructure companies are focused on deploying more compute. We are focused on making increasingly diverse compute work together, and that ambition touches every part of how we build and run this company.
As an early member of the team, you will have significant ownership over your work, partner directly with a small group of highly capable people, and help shape not just what we build, but how we scale the company.
We value people who are excited to work across domains, take ownership of meaningful problems, and help define what Gimlet becomes over the next several years.

Equal Opportunity

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.