Senior AI Infrastructure & GPU Ops Engineer

Accenture PLC; Kirkland (WA); On-site; USD 101,000 - 245,000; Full time

Job summary

Accenture PLC in the United States is seeking a senior infrastructure engineer to design and deploy accelerated-computing infrastructure for AI workloads across on‑premises, cloud, and hybrid environments. You will configure GPU clusters, run Kubernetes-based orchestration, and build reusable automation tools to improve reliability and scale.

The role emphasizes governance, performance validation, capacity planning, and close collaboration with security and data teams.

Qualifications

• Minimum 5+ years of experience designing, deploying, and managing accelerated-computing infrastructure across on-premises, cloud, and hybrid environments.
• Minimum 5+ years of hands‑on experience with accelerated‑computing platforms, including GPUs, DPUs, CPUs, and AI storage architectures.
• Minimum 5+ years of experience with cluster management, workload scheduling, orchestration, observability, and automation.
• Minimum 6 months hands‑on experience with Claude Code, AI automation tools, Terraform, Ansible, Python, and Bash scripting.
• Bachelor's degree or equivalent work experience.

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 workload schedulers and Kubernetes orchestration to support AI training, inference, and HPC workloads.
• Integrate infrastructure platforms with enterprise systems, data platforms, security frameworks, service-management processes, and governance controls.
• Design, build, and maintain reusable tools, scripts, self-service capabilities, and automation workflows for infrastructure operations, including provisioning, configuration management, validation, capacity planning, monitoring, incident management, reporting, and remediation.
• Establish repeatable operational processes for cluster provisioning, configuration management, patching, capacity planning, monitoring, incident response, and lifecycle management.
• Perform and automate GPU, compute, storage, and network benchmarking and validation; diagnose performance issues across multi-node AI training, inference, and distributed compute workloads.
• Develop and maintain architecture diagrams, configuration baselines, operational runbooks, and support documentation.
• Provide technical guidance, troubleshooting, and optimization for GPU clusters supporting AI training, inference, HPC, and multi-node simulation workloads, with emphasis on availability, resiliency, scalability, energy efficiency, and cost management.

Skills

Accelerated‑computing infra

Kubernetes

Slurm

Run:ai

NVIDIA tools

Education

Bachelor's degree

Tools

Kubernetes

Slurm

Run:ai

Terraform

Ansible

Python

Bash

Job description

Accenture PLC in the United States is seeking a senior infrastructure engineer to design and deploy accelerated-computing infrastructure for AI workloads across on‑premises, cloud, and hybrid environments. You will configure GPU clusters, run Kubernetes-based orchestration, and build reusable automation tools to improve reliability and scale.

The role emphasizes governance, performance validation, capacity planning, and close collaboration with security and data teams.