Fluidstack
Technology
NetworkEngineer,Design&Engineering
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Network Engineer, Design & Engineering at Fluidstack. Skills: Network Design, Datacenter Fabrics, RDMA, Lossless Ethernet. Produce end-to-end network architectures. Reason through topology selection”
What You'll Achieve.
Produce deployable network architectures; Produce validated network architectures; Produce optimized network architectures; Ensure designs are technically sound; Ensure designs are physically buildable; Ensure designs are operationally sustainable; Produce network designs for execution without ambiguity; Scale designs to customer target; Meet performance requirements on first turn-up
Industry & Context.
Reason from first principles; Novel design challenges
What They're Looking For.
Must Have
5+ years network engineering experience, Focus on network design and architecture, Designed datacenter network fabrics, Command of datacenter network fundamentals, Understanding of physical layer design, Working knowledge of RDMA network design, Lossless Ethernet configuration
Nice to Have
Hyperscale or large-scale design background, Multi-vendor platform experience, Automation-aware design experience, WAN and interconnect design experience, Startup experience
What You'll Do.
Produce end-to-end network architectures
Reason through topology selection
Reason through rack layout implications
Reason through power constraints
Reason through thermal constraints
Reason through cable plant feasibility
Reason through fabric scaling
Produce design documentation
Design IP addressing schemes
Design routing policy
Design fabric configuration specifications
Design front-end network architectures
Design back-end network architectures
Design storage network architectures
Adapt network architectures
Translate logical designs into physical reality
Consider power distribution constraints
Design structured cabling architecture
Consider cooling airflow
Ensure designs are buildable
Produce comprehensive design packages
Design lossless Ethernet fabrics
Design traffic classes
Understand fabric topology
Understand ECMP behavior
Understand collective communication patterns
Partner with hardware engineering
Partner with DC operations
Partner with software engineering
Partner with validation teams
Participate in design reviews
Lead design review sessions
Contribute to reference architectures
Develop design standards
Develop reusable design patterns
Challenge assumptions
How You'll Work.
Team & Collaboration
Cross-functional partners; Hardware teams; DC Operations; ICT/Structured Cabling; Software Engineering; Validation teams; Non-network stakeholders
Communication Scope
Communicate design intent
Full Job Description
ABOUT FLUIDSTACK We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it. We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI. We hire people who care deeply about this problem space. If that is you, please apply! ABOUT THE ROLE Fluidstack is seeking a Network Engineer, Design & Engineering to join our Network Engineering team. This is a design-ownership role: you will take customer requirements — GPU shape, workload profile, scale targets, tenancy model — and produce end-to-end network architectures that are deployable, validated, and optimized for AI training and inference workloads. This is not a traditional network engineering role. You will own the full design problem space: reasoning through topology selection, rack layout implications, power and thermal constraints, cable plant feasibility, and fabric scaling — all the way from requirements intake through design documentation that deployment teams execute against. Each customer engagement may involve a different GPU platform, a different network topology, and a different set of physical constraints. You must be able to reason from first principles through novel design challenges rather than pattern-match to a single reference architecture. You will work closely with cross-
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