Senior AI Storage Infrastructure Engineer

Job summary

Seeking a Senior AI Storage Infrastructure Engineer to architect high-performance storage solutions for AI-native NeoCloud, focusing on I/O intensive AI model training and inference workloads.

Qualifications

• 5+ years of experience in distributed storage systems and high-performance file systems
• Deep expertise in Kubernetes CSI paradigm and building volume plugins
• Strong experience with block/file I/O at the Linux OS level and performance tuning
• Familiarity with high-throughput networking protocols and their interaction with storage subsystems
• Proven track record of operating and scaling large-scale storage environments
• Experience with infrastructure automation tools and CI/CD pipelines
• Excellent technical communication skills
• Experience in high-velocity, high-growth engineering environments preferred

Responsibilities

• Design, deploy, and maintain Container Storage Interface (CSI) drivers for high-performance parallel file systems
• Architect and implement GPUDirect Storage (GDS) integrations for direct memory access between NVMe drives and GPU memory
• Develop and manage local NVMe caching strategies for low-latency loading of model weights and datasets
• Optimize IOPS, throughput, and latency across the containerized storage stack
• Collaborate with GPU Systems & Fabric team to optimize storage layer for RDMA and high-speed interconnects
• Implement automated monitoring and alerting for storage performance
• Define storage policies, quota management, and multi-tenancy strategies within Kubernetes
• Mentor junior engineers and drive architectural design reviews

Skills

Relocation