Senior Solutions Architect - AI, HPC, & Lustre

Role Description

This is a remote position and can sit anywhere in the United States. All candidates must be willing to very frequently travel across the United States.

NetApp’s Solutions Architecture (SA) team partners with Enterprise Sales to drive advanced AI, analytics, and high-performance computing (HPC) conversations with customers, stepping in when deep technical expertise is required beyond day-to-day SE support. As the Senior Solutions Architect for AI, Analytics & Lustre-based HPC Storage, you will support Enterprise customers across the United States, helping them design and scale AI/ML and data-intensive workloads that depend on ultra-high-performance storage architectures - whether deployed on-premises or across NeoCloud and AI hyperscaler GPU environments.

This role is uniquely focused on NetApp’s high-performance storage solutions for Lustre, a parallel file system widely used in HPC and AI environments to deliver extreme throughput, low latency, and scalable access for GPU clusters and large-scale data processing. You will help customers understand how their data infrastructure, particularly workloads requiring massive bandwidth (e.g., model training, simulations, analytics pipelines), can evolve using NetApp’s Lustre-enabled solutions to eliminate storage bottlenecks and maximize GPU utilization. As customers increasingly leverage NeoCloud and AI hyperscaler providers for GPU-dense compute, you will guide them in architecting storage solutions that span on-prem infrastructure and these cloud-based GPU environments to meet their HPC and AI training demands.

Qualifications

• 7+ years in Solutions Architecture, pre-sales, or customer-facing technical roles with emphasis on AI/ML, HPC, or high-performance data platforms.
• Hands-on experience with:
  • Parallel file systems (Lustre strongly preferred) or other HPC storage architectures
  • GPU-accelerated workloads (NVIDIA ecosystem, distributed training environments)
  • AI/ML frameworks (PyTorch, TensorFlow, or similar)
  • Data-intensive workloads such as simulation, modeling, large-scale analytics, or AI training pipelines
• Core Technical Strengths: Strong Understanding of the Following
  • High-performance storage systems and architectures (block + parallel file systems)
  • Data throughput optimization, I/O bottlenecks, and storage scaling strategies
  • HPC infrastructure including compute, storage, and high-speed networking
  • Knowledge of how parallel file systems enable simultaneous read/write access across distributed nodes, allowing throughput to scale linearly with cluster size.
• Professional Skills:
  • Exceptional communication and ability to translate deep HPC/storage concepts into business value
  • Proven ability to guide customers through complex infrastructure transformations
  • Experience enabling field teams to position differentiated architecture plays (not just features)
  • Strong collaboration across sales, partners, and engineering

Requirements

• Lead advanced discussions with Enterprise customers around AI, analytics, and high-performance computing (HPC) architectures.
• Assess customer environments, focusing on data-intensive workloads, GPU clusters, and performance bottlenecks in storage pipelines.
• Identify opportunities where parallel file systems like Lustre can accelerate AI training, simulation workloads, and large-scale analytics.
• Present architectures spanning GenAI, distributed training pipelines, high-throughput data ingestion, and HPC workflows.
• Help customers architect and optimize HPC and AI storage solutions that bridge on-premises infrastructure with NeoCloud and AI hyperscaler GPU providers (e.g., CoreWeave, Lambda, Crusoe), ensuring high-performance data access regardless of where compute resides.
• Partner with Client Executives and SEs to align AI + HPC + storage strategy with account plans.
• Enable the field to identify and position opportunities involving:
  • GPU saturation challenges
  • AI training data pipelines
  • HPC simulation and research workloads
• Deliver workshops and technical sessions on AI infrastructure design, GPU/storage balance, and Lustre-based architectures.
• Architect high-performance AI and HPC storage solutions leveraging NetApp E-Series and Lustre.
• Provide Design Guidance on:
  • Parallel file systems (Lustre architecture, metadata + object storage separation)
  • High-throughput networking (InfiniBand, RDMA, high-speed Ethernet)
  • GPU cluster integration (NVIDIA DGX, CUDA ecosystems)
  • Data pipelines optimized for large-scale distributed training
  • Storage connectivity and data movement strategies for NeoCloud and AI hyperscaler GPU environments
• Design systems that scale to petabyte-level datasets and extreme throughput requirements typical of AI and HPC.
• Support demos, benchmarks, POCs, and pilot environments demonstrating performance at scale and GPU efficiency gains.
• Drive pipeline growth focused on AI infrastructure modernization and HPC storage transformation.
• Contribute to RFP/RFI responses emphasizing performance, scalability, and architecture differentiation.
• Share insights with product teams to influence NetApp’s evolving AI and HPC storage portfolio.
• Stay Current on Technologies including:
  • Parallel file systems (Lustre, BeeGFS)
  • GPU ecosystems (NVIDIA, CUDA, DGX SuperPOD)
  • AI/ML frameworks (PyTorch, TensorFlow)
  • HPC and AI infrastructure trends
  • NeoCloud and AI hyperscaler GPU ecosystems (e.g., CoreWeave, Lambda, Crusoe) and their evolving storage requirements
• Maintain deep expertise in NetApp high-performance storage (E-Series, EF-Series) supporting Lustre deployments.

Benefits

• Health Insurance
• Life Insurance
• Retirement or Pension Plans
• Paid Time Off
• Various Leave options
• Employee stock purchase plan
• Restricted stocks (RSUs)

Compensation

The target salary range for this position is 197,200 - 255,200 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. The range is based on 'On Target Earnings’ (OTE) representing the total potential earnings, which is the sum of the base salary and potential commission earned when performance targets are achieved. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover various offerings subject to regional variations and governed by local laws, regulations, and company policies. We will provide detailed information about the specific benefits for your region during the recruitment process.