AI Infrastructure Engineer: GPU Clusters & Hybrid Cloud

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

Job summary

Accenture is seeking an experienced Global AI Infrastructure Engineer in Redmond, WA to design and operate GPU‑based clusters for AI training and inference. You will work across bare‑metal and containerized environments, automate workflows, and guide governance, security, and reliability across cloud and hybrid deployments.

The role emphasizes scalable infrastructure, performance tuning, and collaboration with security, data, and operations teams to deliver high‑confidence AI workloads at scale.

Qualifications

• Bachelor's degree or equivalent work experience in a related field.
• 5+ years designing, deploying, and managing accelerated‑computing infra across diverse environments.
• Hands-on experience with GPUs, DPUs, CPUs and AI storage architectures.

Responsibilities

• Design and implement accelerated‑computing infrastructure aligned to architecture and governance.
• Deploy and operate GPU clusters across bare‑metal and container environments with Kubernetes.
• Integrate platforms with security, data and service management processes.
• Develop reusable tools, scripts, and automation for provisioning, monitoring, and remediation.
• Establish repeatable operational processes for provisioning, patching and capacity planning.
• Benchmark and diagnose performance across multi‑node AI workloads and clusters.
• Maintain architecture diagrams, runbooks, and support documentation.
• Provide technical guidance for AI training, inference, HPC and enterprise compute workloads.

Skills

Kubernetes

Terraform

Python

Ansible

CUDA-X

NVIDIA BCM

GPU clusters

Slurm

Run:ai

Security frameworks

Education

Bachelor's degree or equivalent

Tools

NVIDIA BCM

NGC

CUDA-X

NCCL

Dynamo

Run:ai

Job description

Accenture is seeking an experienced Global AI Infrastructure Engineer in Redmond, WA to design and operate GPU‑based clusters for AI training and inference. You will work across bare‑metal and containerized environments, automate workflows, and guide governance, security, and reliability across cloud and hybrid deployments.

The role emphasizes scalable infrastructure, performance tuning, and collaboration with security, data, and operations teams to deliver high‑confidence AI workloads at scale.