AI Infrastructure Consulting Engineer – Converged Compute & Storage

The AI Infrastructure Consulting Engineer – Converged Compute & Storage is responsible for designing, implementing, validating, and supporting high-performance infrastructure solutions that enable enterprise artificial intelligence and machine learning workloads. This client-facing, billable role provides high-quality deliverables and ensures solutions are implemented as designed to the client’s satisfaction and approval. The engineer gains a clear understanding of the client environment, identifies infrastructure requirements, and communicates solutions that align accelerated compute, storage, data movement, resiliency, and operational needs.

• Manage time and expense to meet or exceed expectations defined in the Statement of Work, proactively escalating potential scope, schedule, or budget issues as soon as they are known.
• 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 across diverse customer environments.
• Collaborate with project managers, architects, sales teams, partners, and client stakeholders to manage expectations, dependencies, risks, and timelines.
• Provide technical input for SOWs, ROMs, LOEs, implementation plans, and solution validation when requested.
• Create and maintain accurate project documentation, as-built configurations, test plans, work logs, and client handoff materials.

• Bachelor’s degree and 3 years’ experience delivering complex infrastructure solutions, including planning, implementation, integration, and support OR 7 years experience delivering complex infrastructure solutions, including planning, implementation, integration, and support.
• 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.
• Ability to build and execute implementation and test plans aligned to assigned project deliverables and the Statement of Work.
• Strong written and verbal communication skills with the ability to effectively interact with leadership stakeholders and clients.
• Proven ability to maintain technical documentation and transfer knowledge to clients.
• Demonstrated attention to detail, analytical problem solving, and the ability to balance competing priorities while meeting deadlines.
• Ability and willingness to work beyond regularly scheduled shifts, select weekends, or overtime as necessary to meet operational needs.
• Ability and willingness to travel as needed to CDW locations or client sites.
• Valid U.S. driver’s license.
• Experience with NVIDIA AI Enterprise infrastructure dependencies and validated architectures, is a plus.
• Experience with high-performance data and virtualization platforms, is a plus.
• Familiarity with GPUDirect Storage, RDMA, Kubernetes, Slurm, container runtimes, and AI platform orchestration, is a plus.
• Preferred NVIDIA certifications aligned to the role include NVIDIA-Certified Professional AI Infrastructure (NCP-AII) and NVIDIA-Certified Associate AI Infrastructure…