Network Engineering Lead
IT
San Francisco, CA, USA
About Us
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.
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.
What you will work on
In the first 12-18 months, you will:
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.
You may be a good fit if
You have deep experience designing and operating large-scale data center networks, cloud networks, AI infrastructure networks, HPC networks, or hyperscale network environments.
You understand both external/front-end networking and internal/back-end data center fabrics.
You have hands-on experience with routing, switching, BGP, EVPN/VXLAN, spine-leaf fabrics, WAN/DCI, out-of-band management, optics, structured cabling, and network telemetry.
You can design networks for high availability, high throughput, low latency, operational simplicity, and rapid deployment.
You have operated production networks where uptime, performance, and change discipline matter.
You are comfortable making build-vs-buy decisions, evaluating network vendors, and setting technical standards.
You can partner with deployment, facilities, supply chain, and site teams to turn network designs into working infrastructure.
You are excited to build a team and operating model, not just design architecture on paper.
You communicate clearly with executives, engineers, vendors, deployment teams, and data center operators.
Strong candidates may also have
Experience with AI infrastructure, GPU clusters, InfiniBand, RoCE, RDMA, high-density compute, HPC, or distributed training environments.
Experience designing or operating networks for cloud providers, hyperscalers, neoclouds, colocation environments, or large-scale infrastructure platforms.
Familiarity with NVIDIA networking, high-performance Ethernet fabrics, storage networking, cluster interconnects, and data center interconnect architectures.
Experience building network automation using Python, Go, Ansible, Terraform, NetBox, GitOps workflows, or similar tooling.
Experience building monitoring and telemetry systems for network health, latency, congestion, packet loss, interface errors, and capacity forecasting.
Experience leading network incident response, root cause analysis, and operational improvement programs.
A track record of hiring, mentoring, and leading senior network engineers.
Why join now?
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.
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.