Chief Leading Expert - Next-Gen Storage Media & AI Data Infrastructure

A global research organization is seeking a Chief Architect / Senior Technical Leader to drive the evolution of next-generation storage systems optimized for the AI era.

This role focuses on redefining storage architectures across multiple media types-ranging from high-performance to cost-efficient tiers-to support large-scale AI workloads. The position combines deep expertise in storage systems with strong understanding of AI infrastructure, enabling efficient data pipelines for training, inference, and retrieval-augmented systems.

The successful candidate will lead innovation in heterogeneous storage, near-data computing, and system-level optimization for future data-centric platforms.

Key Responsibilities

Strategic Technical Leadership

• Define long-term technology roadmaps for multi-tier storage systems, including warm and cold data layers.
• Align storage architectures with the full AI data lifecycle, including:

• Data ingestion
• Feature and embedding generation
• Vector indexing and retrieval
• Model inference

• Anticipate industry trends and guide convergence of hardware and software innovations.

Storage Architecture Innovation

• Design next-generation storage architectures addressing bottlenecks in high-latency and large-scale data systems.
• Develop advanced techniques for:

• Data placement and layout
• I/O scheduling and orchestration
• Intelligent caching strategies

• Translate physical media characteristics (latency, endurance, throughput, cost) into optimized system designs.

AI-Driven Storage Optimization

• Bridge storage systems with AI workloads to improve:

• Throughput
• Tail latency
• Reliability

• Design storage-aware optimizations for modern AI pipelines, including:

• Retrieval-augmented generation (RAG) systems
• Embedding storage and vector indexing
• Data tiering and hot/cold data management
• Prefetching and cache reuse strategies

Ecosystem Development & Collaboration

• Lead collaboration with academic institutions and research organizations.
• Foster innovation through partnerships and open research initiatives.
• Translate research breakthroughs into prototypes and production-ready technologies.

• 15+ years of experience in storage systems, including:

• Solid-state storage (e.g., NAND/SSD)
• Distributed or cloud storage systems
• Cold or archival storage technologies

• Proven track record of leading large-scale, high-impact technical projects.

Technical Expertise

• Strong understanding of AI infrastructure, including:

• Large model inference systems
• Cache management strategies
• Vector search and retrieval systems

• Deep expertise in at least one storage domain, with working knowledge of others:

• Flash-based storage
• Cold storage systems
• Emerging non-volatile memory technologies

• Advanced knowledge of storage system design, including:

• Data layout and classification
• Workload profiling
• Tiering strategies
• I/O path optimization
• Scheduling and orchestration

Additional Qualifications

• Strong ability to interpret technology trends and translate them into actionable system strategies.
• Experience with heterogeneous system design and near-data computing concepts.
• Excellent communication skills and ability to influence cross-functional and global teams.
• Experience engaging with senior stakeholders in academia and industry.