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

Chief Architect / Technical Leader – Next-Generation Storage & AI Data Infrastructure

Position Overview

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.

Required Qualifications

• 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.