Senior AI Infrastructure Engineer: GPU Clusters & Automation

Accenture; Irving (TX); On-site; USD 140,000 - 260,000; Full time

Job summary

Accenture is seeking a senior engineer to design and operate accelerated‑computing infrastructure for AI workloads across on‑premises, cloud, and hybrid environments. You will deploy GPU clusters, integrate platforms with security and data systems, and build automation to improve reliability, scalability, and cost efficiency.

The role emphasizes Kubernetes‑driven orchestration, workload scheduling, and automation tools (Terraform, Ansible, Python, Bash) with exposure to NVIDIA ecosystem tools.

Qualifications

• 5+ years designing accelerated-computing infrastructure across on‑premises, cloud, and hybrid environments for various clients.
• Hands-on with GPUs/DPUs/CPUs, high‑bandwidth networks, and AI storage architectures such as parallel file systems, NVMe‑oF, etc.
• 5+ years of cluster management, workload scheduling, orchestration, observability, and automation (Kubernetes, Slurm, Run:ai).
• 6 months hands‑on experience with Claude Code, AI automation tools, Terraform, Ansible, Python, and Bash scripting.
• Bachelor's degree or equivalent work experience (12 years) or more.

Responsibilities

• Design and implement accelerated-computing infrastructure solutions aligned to system architecture, deployment roadmaps, performance, scalability, resiliency, and governance requirements.
• Deploy, configure, and operate GPU-based clusters across bare-metal and containerized environments using schedulers and Kubernetes.
• Integrate infrastructure platforms with enterprise systems, data platforms, security frameworks, service-management processes, and governance controls.
• Build reusable tools and automation workflows for provisioning, configuration, validation, capacity planning, monitoring, and remediation.
• Establish repeatable processes for cluster provisioning, configuration management, patching, capacity planning, and lifecycle management.
• Perform and automate GPU, compute, storage, and network benchmarking and validation; diagnose performance issues across multi-node workloads.
• Develop and maintain architecture diagrams, configuration baselines, runbooks, and support documentation.
• Provide technical guidance, troubleshooting, and optimization for GPU clusters with emphasis on availability, resiliency, energy efficiency, and cost management.

Skills

Kubernetes

Slurm

Run:ai

Python

Terraform

Ansible

GPU clusters

Education

Bachelor's degree or equivalent

Tools

Terraform

Ansible

Python

Bash

BCM/NGC/CUDA-X tools

Job description

Accenture is seeking a senior engineer to design and operate accelerated‑computing infrastructure for AI workloads across on‑premises, cloud, and hybrid environments. You will deploy GPU clusters, integrate platforms with security and data systems, and build automation to improve reliability, scalability, and cost efficiency.

The role emphasizes Kubernetes‑driven orchestration, workload scheduling, and automation tools (Terraform, Ansible, Python, Bash) with exposure to NVIDIA ecosystem tools.