Technical Staff Storage Architect

What you'll do

• Define architectures and translate enterprise customer workload requirements into comprehensive solution designs.
• Architect AI-optimized storage solutions integrating scale-out file, object, and parallel filesystem technologies.
• Influence end-to-end AI infrastructure stacks including software frameworks, compute, networking, and data security.
• Develop solution configurations, BOMs, and SKUs in collaboration with engineering and strategic technology partners.
• Lead investigations into new fabric technologies and storage platforms to support large-scale AI deployments.
• Serve as a technical escalation point for complex development challenges in internal and external forums.
• Generate intellectual property and technology strategy insights to influence multi-year product roadmaps.
• Drive datacenter-level innovation regarding liquid cooling technologies and power density.

What we're looking for

• 10+ years of experience in storage architecture, data platforms, or large-scale distributed systems.
• Expertise in scale-out file/object storage, parallel filesystems, and concepts like NFS/S3, erasure coding, deduplication, and encryption.
• Deep understanding of AI/ML workflows, data pipelines, training/inference patterns, Vector DB, and KV Cache.
• Ability to define storage configurations to meet production-grade performance and SLA requirements.
• Excellent communication skills with experience presenting to cross-functional teams and senior leaders.
• Demonstrated experience working with industry vendors to influence next-generation technology design.
• Ability to translate business outcomes into practical, scalable technical architectures.
• Willingness to travel 20–30%.
• Bachelor’s degree or equivalent experience (preferred).
• Knowledge of AI/ML or HPC performance engineering, including benchmarking and scripting in Python or Bash (preferred).
• Hands-on experience with datacenter technologies like fabrics, cooling, telemetry, or cluster orchestration (preferred).