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Website: fluidstack.com
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Fluidstack is seeking a Reliability Engineer, Data Center Design for a full-time remote position. This role is fundamental to our mission of deploying civilization-scale AI compute infrastructure at unprecedented velocity and scale. Position Summary You'll drive reliability engineering across our next-generation data center portfolio, ensuring facilities meet the rigorous availability standards demanded by frontier AI workloads. Through quantified analysis and statistical rigor, you'll ensure our infrastructure performs where assumptions fall short. Your Responsibilities Design and maintain comprehensive reliability models (reliability block diagrams and fault tree analysis) spanning the full mechanical, electrical, and plumbing infrastructure—from utility intake through rack-level delivery—using Monte Carlo methods at scale to generate precise availability forecasts across multiple confidence levels. Lead independent reliability assessments at pivotal design checkpoints (30% and 90% progress) for Fluidstack's modular facility templates, as well as evaluate third-party proposals and acquisitions using Uptime Institute Tier benchmarks. Partner with external reliability consultants and firms, validating methodologies and converting technical findings into actionable design changes before capital commitment. Steward reliability data, models, and audit documentation within a centralized product lifecycle management platform, generating availability statements, sensitivity analyses, and failure mode reports for lease agreements, service contracts, and stakeholder materials. Synthesize real-world operational data from live sites—failure patterns and repair timelines—into model refinements, compare predicted against measured performance across our operating footprint, and convert insights into maintenance protocols and capital allocation decisions. Skills & Qualifications Proven track record developing reliability block diagrams and fault tree analyses for complex electrical or mechanical systems in high-consequence environments. Working knowledge of Monte Carlo-based availability analysis using industry tools (PTC Windchill Prediction, ReliaSoft, or equivalent), backed by expertise in IEEE 493 and IEEE 3006.5 standards. Experience maintaining reliability models and component failure data in product lifecycle management systems as the authoritative source, not auxiliary spreadsheets. Solid foundation in data center MEP architecture: medium/low voltage distribution, emergency generators, uninterruptible power, thermal loops, cooling distribution systems, and controls infrastructure. You quantify risk naturally—citing availability percentiles and mean time to repair rather than subjective reliability statements. Capability to bridge reliability engineering and business requirements, translating technical findings into language that commercial agreements, SLAs,…
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