Cloud Storage Integration Engineer

To support high-throughput, low-latency storage needs for GPU training and inference, the full-time Cloud Storage Integration Engineer will design and integrate distributed file systems into the GPU cloud while managing the image and driver pipeline in a remote role based in San Jose, CA or Austin, TX. Key Responsibilities Design and integrate distributed/parallel file systems optimized for AI training and inference I/O patterns Own end-to-end distributed-storage integration, including provisioning, multi-tenant isolation, and lifecycle management Tune storage throughput and latency for large-scale parallel access and architect multi-region storage solutions Required Qualifications 3+ years of experience in storage engineering or platform infrastructure, with hands-on experience in distributed/parallel file systems Strong understanding of distributed file system internals, including replication and consistency models Proven experience integrating and operating distributed storage in production environments Performance tuning experience for high-throughput/parallel I/O, with familiarity in NVMe and RDMA storage networking Strong Linux systems knowledge and automation skills, preferably in Python or Go