Solutions Architect - Lead

Solutions Architect - Lead

It's fun to work in a company where people truly BELIEVE in what they're doing!

Job Description: 

Role Summary

We are seeking an experienced AI-focused pre-Sales professional to drive AI, Generative AI, Data Analytics, and Intelligent Data Infrastructure opportunities leveraging NetApp's AI-ready storage and data management portfolio. The role will partner with Sales, Partners, Cloud Providers, and Enterprise Customers to architect AI solutions that accelerate business outcomes while ensuring scalability, security, and data governance.

The ideal candidate will possess strong expertise in AI infrastructure, GPU-based architectures, cloud platforms, storage technologies, and enterprise data management. The individual will act as a trusted advisor for customers embarking on AI transformation initiatives.

Key Responsibilities

AI & Data Infrastructure Consulting

• Engage with customers to understand AI/ML, GenAI, Analytics, and Data Lake requirements.
• Design AI-ready architectures using NetApp storage platforms, cloud services, and GPU infrastructure.
• Advise customers on AI data pipelines, model training environments, and data governance frameworks.
• Position NetApp as the strategic data foundation for AI initiatives.

Technical Pre-Sales Leadership

• Lead customer workshops, discovery sessions, and solution presentations.
• Develop HLDs, LLDs, BoMs, sizing, and technical proposals.
• Support RFI/RFP responses and competitive positioning.
• Conduct Proof of Concepts (PoCs), benchmarks, and technology demonstrations.

AI Solution Architecture

• Architect solutions involving:
  • NVIDIA GPU infrastructure
  • AI Factories
  • RAG architectures
  • Vector databases
  • Data Lakes and Data Fabrics
  • Hybrid and Multi-Cloud AI platforms
  • Kubernetes and MLOps platforms
• Optimize storage performance for AI training and inference workloads.
• Design scalable data pipelines for structured and unstructured data.

Business Development & Enablement

• Support sales teams in opportunity qualification and account strategy.
• Enable field sales and partner teams on AI solutions and use cases.
• Collaborate with hyperscalers, OEMs, and technology partners.
• Evangelize NetApp AI solutions through customer events, webinars, and executive briefings.

Industry & Technology Leadership

• Stay current with AI, GenAI, LLMs, MLOps, DataOps, and cloud-native technologies.
• Track emerging trends in AI infrastructure, storage, and data management.
• Provide market intelligence and customer feedback to product and leadership teams.

Required Technical Skills

AI & Data Platforms

• Generative AI and LLM ecosystems
• RAG frameworks
• Vector databases
• AI/ML lifecycle management
• MLOps and DataOps

Infrastructure

• Enterprise Storage (NetApp ONTAP, AFF, StorageGRID)
• High-Performance Computing (HPC)
• Data Lakes and Data Warehouses
• Backup and Cyber Resilience

Cloud Platforms

• Microsoft Azure AI
• AWS AI/ML Services
• Google Cloud AI Platform
• Hybrid Cloud Architectures

Container & Automation

• Kubernetes
• OpenShift
• Docker
• Terraform
• Ansible

AI Infrastructure

• NVIDIA DGX
• GPU Clusters
• High-speed Networking
• AI Data Pipelines
• Distributed Storage Architectures

Desired Certifications

• NetApp Certified Hybrid Cloud Architect
• NVIDIA AI Infrastructure Certifications
• Microsoft Azure AI Engineer Associate
• AWS Machine Learning Specialty
• Google Professional Machine Learning Engineer
• Kubernetes (CKA/CKAD)

Key Competencies

• Executive-level customer engagement
• Consultative selling
• Solution architecture
• AI business value articulation
• Presentation and storytelling skills
• Competitive analysis
• Cross-functional leadership
• Strategic account management

Preferred Experience

• 12+ years in Enterprise Infrastructure Pre-Sales.
• 5+ years in AI/ML, Data Analytics, Cloud, or HPC solutions.
• Experience supporting large enterprise and strategic accounts.
• Proven track record in driving multi-million-dollar infrastructure and AI transformation deals.

Experience Level

Senior Level