Nashville, TNremote

Salary
$80,400–$266,300from the description
Posted
Jul 7, 2026
Location
Nashville, TN
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

A senior infrastructure engineering role focused on designing, deploying, and operating GPU-accelerated AI infrastructure for enterprise clients across on-premises, cloud, and hybrid environments. Day-to-day work covers cluster management, workload scheduling, model-serving pipelines, and agentic AI platform integration using tools such as Kubernetes, Slurm, and NVIDIA's stack. The role suits experienced infrastructure engineers with deep hands-on knowledge of accelerated computing and significant client-facing or consulting exposure.

Senior level · 5+ years · Remote · Full-time

Must have (11)
AI infrastructure · 5+ yrsKubernetes · 5+ yrsSlurm or Run AiGPU clusters · 5+ yrsInfiniBand or EthernetNVMe or Nvme OfAWS, Azure or GCPPython · 5+ yrsTerraform or AnsibleSONiCVAST, Weka or Ddn
Nice to have (15)
MLOps · 2+ yrsLLMOpsRESTOpenAPIRAGvLLM or SglangTensorRT-LLMTriton Inference ServerNVIDIA DynamoNCCLCUDAMLPerfTensorFlow, PyTorch or JaxCoreWeave or NebiusVMware or Nutanix

“or” means any one of them counts — you don't need all of them.

Posted 5 times — it's one opening, so apply once.

We read this from the posting text with AI. Skim the description below before ruling yourself out.

How this req sits in the market our data

What gives you an edge
InfiniBand10%Terraform11%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
Python51%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $138,970 (middle half $107,524–$175,762). This posting is about at that midpoint.

Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.

Why we read it this way (7)

This role is genuinely hybrid between building/shipping AI infrastructure software (15-1252) and operating/managing infrastructure (15-1244). The JD emphasizes both hands-on deployment and management of GPU clusters AND developing automation, APIs, agentic AI integrations, and MCP servers — the software-building dimension tips it to 15-1252, but 15-1244 is a credible runner-up.

The role is multi-location across many US states (California, Colorado, Illinois, New York, New Jersey, etc.) with no single primary metro; the compensation range shown ($80,400–$266,300/year) spans all listed locations. The wide range reflects both geography and Accenture's internal leveling.

Travel is explicitly required at 25%–100% depending on client need, which is unusual and worth flagging for candidate expectations.

The bachelor's degree requirement is treated as None because the JD explicitly accepts equivalent work experience (minimum 12 years without a degree, or 6 years with an Associate's degree).

NVIDIA platform tools (BCM, NGC, NVLink, NVMe-oF, NCCL, CUDA, TensorRT-LLM, vLLM, SGLang, Triton, Dynamo, llm-d, MLPerf, fio, iperf) appear in both the required responsibilities narrative AND the preferred qualifications section. Because they are framed as 'experience using' under Preferred Skills, they are marked preferred; the required section describes them as deployment tasks rather than gating on prior tool experience explicitly.

Slurm and Run:ai are listed together as interchangeable workload schedulers in the required section and are captured as alternatives of each other.

VAST, Weka, and DDN are listed as alternative AI storage platforms; VAST is used as the primary name with the others as alternatives.

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