Job Title: Storage Engineer
About Hydra Host
Hydra Host is a Founders Fund-backed NVIDIA cloud partner building the infrastructure platform that powers AI at scale. We 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.