Job Overview
Location
U.S. Remote
Job Type
Full-time
Category
DevOps
Date Posted
June 30, 2026
Full Job Description
📋 Description
- • Lead on-call escalations for critical data center incidents, triaging issues virtually with deep system knowledge to guide field teams without overwhelming them.
- • Travel to data center sites 50%+ of the time to respond to live incidents, conduct post-incident reviews on-site, and implement operational improvements directly in the field.
- • Own end-to-end root cause analysis (RCA) for significant operational events, ensuring corrective actions eliminate entire classes of failure—not just isolated incidents.
- • Analyze patterns across fleet-wide incidents and RCAs to identify the highest-value learnings, prioritizing actions that deliver maximum reliability impact while avoiding scope creep.
- • Transfer proven operational practices and fixes from one data center campus to another, ensuring solutions become standardized across the entire fleet before failures recur.
- • Design, write, and enforce the operational assessment standard, auditing each campus against it and feeding findings directly into the corrective action loop.
- • Build operational frameworks from scratch, including assessment, audit, qualification, and training programs, rather than inheriting legacy systems.
- • Operate at scale equivalent to a G7 nation’s electricity consumption, managing infrastructure targeting 100 GW by the end of the decade.
- • Function in a live construction environment, maintaining flawless operations while data centers are actively being built and scaled.
- • Define and evolve the company’s operational model as it scales 100x, setting standards that will be adopted by thousands of future team members.
- • Maintain extreme ownership of operational outcomes, often expanding scope beyond core responsibilities to ensure issues are resolved end-to-end.
- • Apply first-principles thinking to challenge existing assumptions, rejecting analogies and prioritizing the best solution regardless of origin.
- • Drive velocity by acting with urgency and intensity, contributing to long hours and high-pressure environments focused on accelerating AI infrastructure deployment.
- • Cultivate a culture of love for the mission, recognizing that building civilization-scale AI infrastructure is the most critical technical challenge of our time.
🎯 Requirements
- • Proven experience running live critical data center operations and leading teams of operators under high-stakes conditions.
- • Demonstrated ability to triage complex incidents remotely, knowing precisely when to escalate and when to empower field teams to resolve issues independently.
- • Extensive track record of authoring root cause analyses that eliminate systemic failure classes, not just individual incidents, and tracking corrective actions to full closure.
- • Experience auditing operational sites against self-authored standards and holding consistent performance bars across geographically dispersed locations.
- • History of traveling extensively between data center sites to implement improvements, transfer best practices, and leave each location better than found.
- • Proven ability to build operational assessment, audit, or training programs from scratch without relying on inherited systems.
🏖️ Benefits
- • Competitive total compensation package including salary and equity.
- • Retirement or pension plan aligned with local norms.
- • Health, dental, and vision insurance.
- • Generous PTO policy aligned with local norms.
Skills & Technologies
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About FluidStack Inc.
FluidStack Inc. operates a distributed cloud platform that aggregates under-utilized GPUs in data centers and individual machines worldwide, renting them on-demand to AI researchers, startups, and enterprises for training and inference workloads. The company automates deployment, security, and billing, offering prices up to 80% below traditional hyperscalers while providing instant access to high-end NVIDIA A100, H100, and consumer GPUs through a single API and web console. Headquartered in London, FluidStack targets machine-learning engineers who need scalable, low-cost compute without long-term commitments, claiming thousands of active nodes and customers including Fortune 500 enterprises and leading research labs.
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