Hybrid Senior Field Solutions Architect, AI/HPC

at CDW

• Job title: Senior Field Solutions Architect, AI/HPC
• Job type: Full Time
• Experience level: Senior
• Salary: $145,600 - $203,840 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Kubernetes
• Location requirements: Hybrid, Toronto, Canada

About the role

• Senior Field Solutions Architect at CDW designing AI and HPC architectures for customers. Leading presales engagements to provide effective technology solutions in advanced computing.

Responsibilities

• Lead discovery to translate business outcomes into technical requirements and reference architectures for AI/HPC platforms (GPU clusters, distributed training, model serving, orchestration).
• Design scalable compute using leading GPU technologies; specify low-latency fabrics (InfiniBand, RoCE) and high-performance storage (e.g., NVMe, parallel file systems).
• Define security, resilience, data-management, and cost-optimization patterns; document assumptions and trade-offs.
• Build solution designs, sizing guidance, diagrams, and BOMs with clear scope boundaries and delivery alignment.
• Support proposals, statements of work, and risk identification; ensure feasibility with delivery leadership.
• Present technical content to diverse audiences (engineers to executives) and handle deep-dive Q&A.
• Act as a trusted advisor on workload placement, performance tuning considerations, and modernization paths.
• Partner with account managers to qualify opportunities and position the right mix of products, professional services, and managed services.
• Coordinate architecture validation with key vendors; stay current on roadmaps affecting AI/HPC platform choices.
• Collaborate with professional services and project management so designs are deployable and milestones are clear.
• Contribute reusable assets (templates, calculators, patterns) and improve architecture quality through peer reviews.
• Advocate for accurate opportunity data and case hygiene to support forecasting and delivery planning.

Requirements

• Hands-on presales architecture experience designing AI/HPC infrastructure: GPU-accelerated compute, distributed training, model serving, high-performance storage, and low-latency networking.
• Strong consulting fundamentals: discovery, requirements translation, executive-ready communication, and decision framing.
• Proficiency creating architecture diagrams, BOMs, sizing, and cost/comparison analyses.
• Demonstrated collaboration across delivery, program/project management, managed services, and vendor partners.
• Ability to simplify complexity, build stakeholder confidence, and drive consensus.
• Familiarity with orchestration and scheduling (Kubernetes, Slurm, PBS); parallel file systems (Lustre, BeeGFS); object storage; and benchmarking/performance methods.
• Exposure to MLOps/ModelOps pipelines, inference serving, RAG infrastructure, or data-platform integration.
• Industry knowledge in research, public sector, or enterprise analytics use cases.

Benefits

• Health insurance
• Professional development opportunities