AI Infrastructure Consulting Engineer – Converged Compute, Storage

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee time and expenses to ensure they meet or exceed the expectations outlined in the Statement of Work, proactively addressing potential scope, schedule, or budget concerns.

• Deploy and integrate accelerated compute and high-performance storage solutions for AI training, fine-tuning, inference, and data-intensive tasks.

• Conduct discovery, installation, configuration, migration, validation, benchmarking, troubleshooting, and knowledge transfer across various customer environments.

• Work collaboratively with project managers, architects, sales teams, partners, and client stakeholders to manage expectations, dependencies, risks, and timelines.

• Offer technical insights for Statements of Work (SOWs), Rough Order Magnitudes (ROMs), Levels of Effort (LOEs), implementation strategies, and solution validation.

• Develop and sustain precise project documentation, including as-built configurations, test plans, work logs, and client handoff materials.

• Design, implement, validate, and support high-performance infrastructure solutions tailored for enterprise AI and machine learning applications.

• Comprehend client environments, pinpoint infrastructure necessities, and communicate solutions that align accelerated compute, storage, data movement, resiliency, and operational requirements.

⛳️ Requirements

• Bachelor’s degree with 3 years of experience in delivering complex infrastructure solutions, encompassing planning, implementation, integration, and support OR 7 years of experience in the same fields.

• Proven experience in installing, configuring, upgrading, and troubleshooting enterprise compute and storage infrastructures.

• Familiarity with accelerated computing platforms such as NVIDIA DGX, HGX, or similar GPU-based systems.

• Understanding of AI workload characteristics, including data ingestion, checkpointing, training, fine-tuning, inference, and model artifact management.

• Experience with high-performance or scale-out storage architectures and protocols like NFS, SMB, object storage, parallel file systems, and NVMe-based solutions.

• Proficient in Linux administration, firmware and driver dependencies, system validation, health checks, and performance troubleshooting.

• Capability to develop and execute implementation and test plans in alignment with assigned project deliverables and the Statement of Work.

• Excellent written and verbal communication skills, with the ability to interact effectively with leadership stakeholders and clients.

• Proven track record of maintaining technical documentation and transferring knowledge to clients.

• Strong attention to detail, analytical problem-solving skills, and the ability to manage competing priorities while adhering to deadlines.

• Willingness to work beyond regular hours, including weekends or overtime as required to fulfill operational needs.

• Availability to travel as necessary 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.

• Familiarity with high-performance data and virtualization platforms is a plus.

• Knowledge of GPUDirect Storage, RDMA, Kubernetes, Slurm, container runtimes, and AI platform orchestration is a plus.

• Preferred NVIDIA certifications relevant to the role include NVIDIA-Certified Professional AI Infrastructure (NCP-AII) and NVIDIA-Certified Associate AI Infrastructure and Operations (NCA-AIIO) is a plus.

🏝️ Benefits

• Annual bonus target of 10% subject to the terms and conditions of the plan.

• Benefits overview: https://cdw.benefit-info.com/

• Flexible remote work arrangements.

• Salary ranges may vary based on geographic differentials.