Manager, HPC Storage Engineer (Akuhaito H.S.Comp)

Runpod is pioneering the future of AI and machine learning, offering cutting-edge cloud infrastructure for fullstack AI applications. Founded in 2022, we are a rapidly growing, wellfunded, remotefirst company with a global team across the US, Canada, and Europe. Our mission is to create a foundational platform that enables developers and companies to build, deploy, and scale custom AI systems with speed and flexibility. As AI workloads continue to push the limits of throughput, latency, and parallelism, Runpod is investing heavily in next-generation storage architectures purpose-built for GPU-centric compute. We are looking for an Engineering Manager, Datacenter Storage Engineering to lead the team responsible for Runpods distributed storage infrastructure across all regions. This role owns the end-to-end storage stack from NAND and NVMe devices through filesystems, transport protocols, and cluster-level deployment ensuring performance, reliability, and scalability for AI workloads. You will manage engineers designing and operating large-scale SAN and NFS-based systems, including high-performance shared filesystems for training workloads. This role requires deep technical fluency and architectural leadership, combined with robust people management and operational discipline. Responsibilities Own Distributed Storage Architecture: Define, evolve, and operate Runpods global storage platforms, supporting training, inference, checkpointing, and dataset access at scale. Build the Storage Engineering Team: Manage and grow a team of storage and systems engineers. Set clear ownership, technical direction, and operational standards across regions. High-Performance Shared Filesystems: Design and operate large-scale SAN and NFS deployments, including performance-sensitive shared storage for GPU clusters.= Advanced Filesystems & Platforms: Lead deployments and operations of VAST Data and experience with Lustre or similar parallel filesystems used in HPC and AI envi .