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. This gives our team access to systems research problems grounded in frontier models, cutting-edge production workloads, and emerging hardware architectures.
About the role
Gimlet Labs is seeking a Data Center Facilities Operations Lead to own the critical facilities operating model for Gimlet data centers and high-density AI infrastructure deployments. In this role, you will make sure the facility-side systems that support Gimlet's compute capacity are ready, monitored, maintained, and operating inside the required envelope.
You will focus on the infrastructure that keeps liquid-cooled AI systems healthy: facility water loops, CDUs, supply and return temperatures, flow, pressure, water quality, leak detection, alarms, heat rejection, power and cooling coordination, BMS/DCIM telemetry, maintenance procedures, and vendor repair workflows.
This role is well-suited for a critical facilities operator who understands data center MEP systems, liquid cooling, operational monitoring, and the discipline required to keep high-density compute environments stable as Gimlet scales.
What success looks like
In the first 12-18 months, you will:
Build the facilities operations model for current and future Gimlet sites, including operating standards, escalation paths, maintenance routines, acceptance criteria, and facility readiness gates.
Translate OEM and engineering requirements for liquid-cooled platforms into practical site operating envelopes for temperature, flow, pressure, water quality, alarms, and heat rejection.
Own monitoring and response for facility-side telemetry, including supply and return water temperatures, delta-T, flow, pressure, leak detection, CDU status, cooling capacity margins, and BMS/DCIM alarms.
Partner with colocation providers, facility vendors, OEMs, Site Managers, Data Center Technicians, Deployment Leads, and TPMs to ensure facilities are ready before new compute capacity is deployed.
Create and maintain MOPs, SOPs, EOPs, maintenance windows, runbooks, inspection routines, and incident response procedures for critical facilities and liquid cooling operations.
Coordinate preventive maintenance, repairs, and vendor response for CDUs, facility water loops, filters, valves, pumps, sensors, leak detection systems, chillers, dry coolers, CRAHs, and related infrastructure.
Lead facility-side root cause analysis for thermal, leak, power, cooling, monitoring, and environmental events, then drive durable corrective actions.
Build reporting that shows facility health, risk, readiness, capacity margin, recurring issues, open repairs, and operational trends across Gimlet sites.
You may be a good fit if
You have experience in data center facilities operations, critical facilities engineering, MEP operations, commissioning, facilities maintenance, or high-density infrastructure operations.
You understand liquid cooling operations, facility water systems, CDUs, heat rejection, supply and return temperature management, flow, pressure, filtration, leak detection, and water quality controls.
You have operated or supported BMS, DCIM, EPMS, CDU monitoring, alarm response, trend analysis, and facilities telemetry in production environments.
You can write and run MOPs, SOPs, EOPs, maintenance plans, incident procedures, and vendor repair workflows with strong operational discipline.
You communicate clearly with site teams, network teams, deployment TPMs, engineering, colocation providers, OEMs, and facilities vendors.
You are comfortable working in active data center environments and supporting urgent facilities escalations when they arise.
Strong candidates may also have
Experience supporting GPU clusters, GB200/GB300-class platforms, NVL rack-scale systems, HPC environments, AI infrastructure, or other high-density liquid-cooled compute deployments.
Experience with data center commissioning, integrated systems testing, site acceptance testing, facility turnover, or deployment readiness reviews.
Familiarity with power distribution, UPS/generator coordination, chilled water systems, dry coolers, CRAH/CRAC systems, CDUs, rear-door heat exchangers, and liquid cooling safety practices.
Experience managing colocation provider obligations, service levels, maintenance windows, vendor escalations, and facilities contract deliverables.
A track record of improving facility reliability through monitoring, preventive maintenance, incident analysis, documentation, training, and operational controls.
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.
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