Job Overview
Location
New York, NY
Job Type
Full-time
Category
Product Management
Date Posted
July 6, 2026
Full Job Description
đź“‹ Description
- • Deploy and validate data center network infrastructure including front-end, back-end, BMS, and management systems by configuring switches, installing and validating optical transceivers, and coordinating cabling to ensure full fabric convergence.
- • Ensure physical connectivity meets production-grade standards by coordinating fiber remediation, validating insertion loss and OTDR traces, and troubleshooting optical-layer issues to prevent outages at scale.
- • Manage end-to-end hardware logistics including device staging, rack/stack coordination, RMA processing, DCIM updates, inventory tracking, and vendor shipment scheduling to ensure hardware readiness for deployments.
- • Partner with DC Operations, ICT, Hardware, and Network Engineering teams to identify and escalate blockers early, align cross-functional efforts, and maintain momentum during high-intensity deployment cycles.
- • Maintain accurate cutsheets, as-builts, validation results, and lessons learned documentation to continuously improve the deployment playbook and enable team scalability.
- • Provide operational support during and after deployments including incident response, break-fix troubleshooting, and real-time resolution of network connectivity issues across complex topologies.
- • Automate repetitive tasks by converting manual processes into software tools; any task performed twice by hand is expected to be automated to reduce human error and increase velocity.
- • Execute deployments with extreme ownership, often taking on scope beyond core responsibilities to ensure timelines are met and infrastructure is delivered flawlessly.
- • Travel 50–60% of the time to onsite deployment locations across the U.S. to support rapid data center turn-up at new sites every few months.
- • Configure and validate modern network fabrics including EVPN/VXLAN, BGP, and CLOS architectures in production environments with tens of thousands of links.
- • Validate every optical link for cleanliness, signal integrity, and error-free performance before any AI training job is allowed to run on the fabric.
- • Use tooling and automation to eliminate manual cutsheets and reduce deployment queues, ensuring zero tolerance for "close enough" in infrastructure readiness.
- • Document all configurations, test results, and operational procedures with precision to support auditability, knowledge transfer, and future scaling.
- • Work at high intensity in a fast-paced environment where speed and scale are the primary differentiators, often under tight deadlines to deploy gigawatts of compute infrastructure.
🎯 Requirements
- • Hands-on experience deploying and configuring production-grade data center network infrastructure, including switches and modern fabrics (EVPN/VXLAN, BGP, CLOS)
- • Proven ability to troubleshoot across physical and logical layers, including OTDR traces, insertion loss, BGP sessions, and complex network topologies
- • Willingness and ability to travel 50–60% for onsite deployments across the U.S.
- • Experience managing hardware logistics: staging, rack/stack, RMA, DCIM, inventory, and vendor coordination
- • Strong documentation skills with a focus on cutsheets, as-builts, validation results, and deployment playbooks
- • Comfort working in high-velocity environments with extreme ownership and autonomy, often taking on scope beyond core role
🏖️ 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
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
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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