Storage Engineer

Location Miami, United States# Storage Engineer at Hydra Host Location Miami , United States Salary $200000 - $300000 /year

Job Type Full-time

Date Posted November 18th, 2025

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Job Title:

Storage Engineer
** About Hydra Host
** Hydra Host is a Founders Fund-backed NVIDIA cloud partner building the infrastructure platform that powers AI  connect AI Factories - high-performance GPU data centers - with the teams that depend on them: research labs training foundation models, enterprises running production inference, and developer platforms demanding scalable compute capacity.  Hydra Host is building the next-generation bare-metal GPU infrastructure network and marketplace under its Brokkr platform.

The company enables independent data centers to monetize GPU capacity while providing enterprises with scalable, high-performance access to NVIDIA-based compute (e.g., H100, H200, B200, L40S, RTX 4090). As we expand our infrastructure capabilities, Hydra Host is now seeking a Storage Engineer to lead the architecture, development, and deployment of our next-generation AI/HPC storage platform.
*
* The role:

** As a Storage Engineer, you will be responsible for designing and building Hydra Host’s first production-grade storage platform from the ground up, supporting the company’s rapidly expanding network of bare-metal GPU clusters.

You’ll own the architecture, technology selection, implementation, and evolution of this platform, defining how Hydra Host manages data for large-scale, distributed AI workloads across global data centers.

This is a senior, hands-on role for an engineer who has built storage systems for GPU clusters before, with deep expertise in both block and object storage and a strong understanding of parallel file systems, performance optimization, and large-scale orchestration.
** Key Responsibilities*
* · Define, architect, and implement Hydra Host’s first production storage platform tailored for bare-metal GPU clusters and AI/HPC workloads.
· Lead all technical decisions around storage stack design, from hardware infrastructure to parallel file system orchestration and performance tuning.
· Select, build, and maintain storage solutions spanning both block (NVMe, SAN, Ceph, etc.) and object storage (S3-compatible, custom, or Ceph Object Gateway) layers.
· Design for high-throughput, low-latency access, supporting large datasets, rapid checkpointing, and parallel access for distributed AI training workloads.
· Integrate and optimize parallel file systems such as Lustre, BeeGFS, Spectrum Scale, WekaIO, or CephFS, ensuring maximum performance and fault tolerance.
· Ensure compatibility across Hydra’s diverse GPU/OEM ecosystem, accounting for unique firmware, BMC/Redfish APIs, and hardware configurations.
· Develop automation, observability, and management tooling for storage, focusing on reliability, scalability, and efficiency.
· Act as a builder and architect: deeply hands-on in deployment, troubleshooting, and optimization, while guiding long-term storage roadmap.
· Collaborate cross-functionally with GPU, HPC, and platform engineering teams to integrate storage with compute and network layers.
· Interface with customers and product leadership to define feature priorities, performance benchmarks, and future enhancements.
** Must-Have Qualifications*
* · 8+ years of progressive, hands-on experience designing and implementing high-performance storage systems for compute clusters in HPC, AI, or bare-metal cloud environments.
· Proven track record building storage infrastructure from scratch, not just operating existing systems.
· Deep expertise in block storage (NVMe, SAN, Ceph, distributed block systems) and object storage (S3, MinIO, Ceph Object Gateway, etc.).
· Strong background in parallel file systems (WekaIO, BeeGFS, Lustre, Spectrum Scale, or similar) supporting GPU or AI cluster workloads.
· Solid foundation in Linux systems engineering, automation, and scripting for distributed environments.
· Familiarity with BMC, Redfish APIs, and OEM server firmware for bare-metal management.
· Deep understanding of AI/ML data pipelines: model checkpointing, data locality, and multi-tiered storage optimization.
· Excellent problem-solving, debugging, and communication skills, able to translate technical decisions into clear architectural direction.
** Preferred Qualifications*
* · Experience building storage solutions for large-scale GPU or HPC infrastructure.
· History of technical leadership or mentorship, growing teams or owning a product roadmap.
· Experience evaluating and managing vendor relationships and negotiating storage hardware/software contracts.
· Contributions to open-source HPC or storage projects (Ceph, Lustre, BeeGFS, etc.).
· Familiarity with confidential computing, secure data handling, or high-availability architectures.
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