AI Infrastructure Consulting Engineer – Converged Compute & Storage

CDW

1d • $77,725 - $108,265

About The Position

The AI Infrastructure Consulting Engineer – Converged Compute & Storage designs, implements, validates, and supports high-performance infrastructure solutions for enterprise AI and machine learning workloads. This client-facing, billable role delivers high-quality work and ensures solutions are implemented as designed to the client’s satisfaction and approval. The engineer develops an understanding of client environments and requirements, then communicates solutions that align accelerated compute, storage, data movement, resiliency, and operational needs.

The role includes implementing and integrating accelerated compute and high-performance storage for AI training, fine-tuning, inference, and data-intensive workloads. The engineer performs discovery, installation, configuration, migration, validation, benchmarking, troubleshooting, and knowledge transfer across customer environments. They work with project managers, architects, sales teams, partners, and client stakeholders to manage expectations, dependencies, risks, and timelines, and may provide technical input for project estimates, plans, and solution validation. The engineer also maintains project documentation and client handoff materials.

CDW describes itself as a Fortune 500 technology solutions provider serving business, government, education, and healthcare organizations. It emphasizes collaboration, learning, responsible engagement with AI, and an equitable, transparent, and respectful hiring process.

Requirements

• Bachelor’s degree and 3 years of experience delivering complex infrastructure solutions, including planning, implementation, integration, and support; alternatively, 7 years of such experience.
• Demonstrated experience installing, configuring, upgrading, and troubleshooting enterprise compute and storage infrastructure.
• Working knowledge of accelerated computing platforms, including NVIDIA DGX, HGX, or comparable GPU-based systems.
• Understanding of AI workload characteristics, including data ingest, checkpointing, training, fine-tuning, inference, and model artifact management.
• Experience with high-performance or scale-out storage architectures and protocols such as NFS, SMB, object storage, parallel file systems, and NVMe-based solutions.
• Experience with Linux administration, firmware and driver dependencies, system validation, health checks, and performance troubleshooting.
• Strong written and verbal communication skills and ability to interact effectively with leadership stakeholders and clients.
• Proven ability to maintain technical documentation and transfer knowledge to clients.
• Attention to detail, analytical problem-solving ability, and ability to balance competing priorities while meeting deadlines.
• Ability and willingness to work beyond regularly scheduled shifts, select weekends, or overtime as needed to meet operational needs.
• Ability and willingness to travel as needed to CDW locations or client sites.
• Valid U.S. driver’s license.

Nice To Haves

• Experience with NVIDIA AI Enterprise infrastructure dependencies and validated architectures.
• Experience with high-performance data and virtualization platforms.
• Familiarity with GPUDirect Storage, RDMA, Kubernetes, Slurm, container runtimes, and AI platform orchestration.
• Preferred NVIDIA certifications aligned to the role: NVIDIA-Certified Professional AI Infrastructure (NCP-AII) and NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO).

Responsibilities

• Manage time and expenses to meet or exceed Statement of Work expectations, and promptly escalate potential scope, schedule, or budget issues.
• Implement and integrate accelerated compute and high-performance storage solutions for AI training, fine-tuning, inference, and data-intensive workloads.
• Perform discovery, installation, configuration, migration, validation, benchmarking, troubleshooting, and knowledge transfer in customer environments.
• Collaborate with project managers, architects, sales teams, partners, and client stakeholders to manage expectations, dependencies, risks, and timelines.
• Provide technical input for Statements of Work (SOWs), ROMs, LOEs, implementation plans, and solution validation when requested.
• Create and maintain project documentation, as-built configurations, test plans, work logs, and client handoff materials.
• Build and execute implementation and test plans aligned with assigned project deliverables and the Statement of Work.
• Transfer technical knowledge to clients.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level