ZipRecruiter

Log In

Fluidstack

60 Fluidstack Network Engineer Jobs Hiring Near You

Fluidstack

Lead, Network Connectivity & Strategy

San Diego, CA · On-site

$107K - $148K/yr

About Fluidstack We exist to make humanity more free. For most of human history, you farmed or you ... This role sits at the intersection of network engineering, infrastructure planning, and commercial ...

Fluidstack

Lead, Network Connectivity & Strategy

Austin, TX · On-site

$100K - $138K/yr

About Fluidstack We exist to make humanity more free. For most of human history, you farmed or you ... This role sits at the intersection of network engineering, infrastructure planning, and commercial ...

Fluidstack

Lead, Network Connectivity & Strategy

New York, NY · On-site

$111K - $153K/yr

About Fluidstack We exist to make humanity more free. For most of human history, you farmed or you ... This role sits at the intersection of network engineering, infrastructure planning, and commercial ...

Fluidstack

Platform Engineer

San Francisco, CA · On-site

Job Summary : Fluidstack is a leading cloud provider focused on building civilization-scale ... assets, network topology, and configuration data • Create DCIM platforms for rack operations ...

next page

Showing results 1-20

All JobsFluidstack JobsFluidstack Network Engineer Jobs

Fluidstack Jobs Information

What other companies are hiring for Network Engineer jobs?
What are the most popular jobs at Fluidstack?
What are the most popular categories at Fluidstack?
Infographic showing various Network Engineer job openings at Fluidstack in the United States as of July 2026, with employment types broken down into 98% Full Time, and 2% Contract. Highlights an 91% Physical, and 9% Remote job distribution.

Network Engineer, Design & Engineering

Fluidstack

Austin, TX • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
Fluidstack is focused on delivering cutting-edge compute infrastructure for AI, aiming to enhance human freedom through technology. They are seeking a Network Engineer, Design & Engineering to take ownership of network design for AI training and inference workloads, collaborating with cross-functional teams to create deployable and optimized network architectures.
Responsibilities:
• Own the design lifecycle from customer requirements through deployable architecture.
• Produce topology designs, IP/addressing schemes, routing policy, and fabric configuration specifications for AI training and inference fabrics.
• Design front-end (out-of-band management, customer access), back-end (GPU-to-GPU training fabric), and storage network architectures.
• Design network architectures that adapt to different GPU platforms (NVIDIA, AMD, custom accelerators), server form factors, and workload profiles.
• Translate logical network designs into physical reality.
• Work cross functionally on rack elevation planning, power distribution constraints, structured cabling architecture, and cooling/airflow considerations.
• Produce comprehensive design packages that enable deployment teams to execute independently.
• Design lossless Ethernet fabrics optimized for RDMA (RoCEv2) workloads including PFC configuration, ECN tuning, traffic class design, and congestion management.
• Partner with Hardware Engineering on server/GPU platform integration, DC Operations on facility constraints and power planning, ICT on structured cabling feasibility, Software Engineering on automation requirements, and Validation teams on test plans and acceptance criteria.
• Participate in and lead design review sessions.
• Contribute to the development of reference architectures, design standards, and reusable design patterns that accelerate future deployments.
Qualifications:
Required:
• 5+ years of network engineering experience with a demonstrated focus on network design and architecture rather than purely operational roles.
• Experience designing datacenter network fabrics from requirements through deployment.
• Strong command of datacenter network fundamentals including CLOS/fat-tree topologies, BGP (eBGP underlay, iBGP/eBGP overlay), EVPN/VXLAN, IP addressing and subnetting at scale, and physical layer design (optics selection, fiber types, link budgets).
• Working knowledge of RDMA network design (InfiniBand and/or RoCEv2), lossless Ethernet configuration (PFC, ECN, DCQCN), and the network performance requirements of distributed AI training workloads.
• Experience designing networks around specific GPU platforms (NVIDIA DGX/HGX, AMD MI-series, custom accelerator platforms).
• Ability to reason about network design in the context of physical constraints.
• Break complex design problems into fundamental components and reason through them systematically.
• Produce design documentation that is clear, complete, and actionable.
• Excellent at working across engineering disciplines and communicate design intent clearly to non-network stakeholders.
Preferred:
• Experience designing networks at hyperscale companies (Meta, Google, Microsoft, AWS) or large AI infrastructure providers.
• Deep familiarity with multiple network hardware platforms (Arista, Juniper, NVIDIA/Mellanox, Broadcom-based).
• Experience designing networks with automation in mind — consistent naming conventions, structured data models, templatable configurations.
• Experience with WAN topology design, DCI (Data Center Interconnect), optical transport, and backbone network architecture.
• Experience in a high-growth infrastructure or cloud company.
Company:
Fluidstack accelerates the world’s most ambitious AI projects by removing the bottlenecks to compute. Founded in 2017, the company is headquartered in London, GBR, with a team of 51-200 employees. The company is currently Growth Stage.

Apply