AI Infrastructure & GPU Compute Engineer

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

Job summary

Accenture is seeking an experienced Global AI Infrastructure engineer to design and operate accelerated-computing infrastructure for AI training, inference and HPC across on‑premises, cloud and hybrid environments.

You will deploy GPU-based clusters, implement automation, integrate with security and governance, and develop runbooks and tooling to improve reliability, scalability, and cost efficiency.

Qualifications

• 5+ years designing, deploying and managing accelerated-computing infra across on-prem/cloud/hybrid environments.
• Hands-on experience with GPUs, DPUs, CPUs and AI storage architectures.
• Experience with Kubernetes, Slurm, Run:AI and automation tooling.

Responsibilities

• Design and implement accelerated-computing infra aligned to architecture, roadmaps, performance and governance.
• Deploy and operate GPU-based clusters in bare-metal and containerized environments.
• Integrate platforms with security, data and governance controls.
• Build reusable tools, scripts and automation for provisioning, monitoring and incident management.
• Establish repeatable processes for cluster provisioning, patching, capacity planning and lifecycle management.
• Benchmark and validate GPU, compute, storage, and network performance for AI workloads.
• Develop architecture diagrams, runbooks and support documentation.
• Provide guidance and optimization for AI training, inference, HPC, and enterprise compute workloads.

Skills

GPU clusters

Kubernetes

Python

Bash scripting

Terraform

Ansible

Education

Bachelor's degree or equivalent

Tools

Slurm

Run:AI

Terraform

Ansible

Job description

Accenture is seeking an experienced Global AI Infrastructure engineer to design and operate accelerated-computing infrastructure for AI training, inference and HPC across on‑premises, cloud and hybrid environments.

You will deploy GPU-based clusters, implement automation, integrate with security and governance, and develop runbooks and tooling to improve reliability, scalability, and cost efficiency.