Senior AI Infra Engineer - GPU Clusters & HPC Ops

Accenture; Boston (MA); On-site; USD 94,000 - 245,000; Full time

Job summary

Accenture is seeking an experienced Global AI Infrastructure engineer to design and operate large-scale GPU clusters across on-prem, cloud, and hybrid environments. You will implement automated tooling, improve performance, and ensure governance and cost efficient operations.

Travel 25-60% may be required; 5+ years with GPUs, Kubernetes, and automation is expected. This role is based in Massachusetts with competitive benefits and career growth opportunities.

Qualifications

• Minimum 5+ years designing, deploying accelerated infrastructure across on-prem, cloud, and hybrid.
• Hands-on with GPUs/DPUs, high-bandwidth networks, AI storage architectures.
• 5+ years with cluster management, orchestration, automation (Kubernetes, Slurm, Run:AI).

Responsibilities

• Design and implement accelerated-computing infrastructure aligned to architecture and governance.
• Deploy GPU-based clusters across bare-metal and containerized environments using Kubernetes.
• Integrate infrastructure with security, data platforms, and operations processes.
• Build reusable tools and automation workflows for provisioning, monitoring, and remediation.
• Establish repeatable processes for provisioning, patching, and lifecycle management.
• Benchmark and diagnose performance across multi-node AI training workloads.
• Develop architecture diagrams, runbooks, and support documentation.
• Provide guidance and optimization for GPU clusters supporting AI training/inference.

Skills

Kubernetes

Python

Terraform

Ansible

Slurm

Bash

GPU clusters

Run:ai

Education

Bachelor's degree or equivalent (minimum 12 years) work experience

Tools

Kubernetes

Slurm

Terraform

Ansible

Python

Bash

NVIDIA tools (NGC, BCM)

Job description

Accenture is seeking an experienced Global AI Infrastructure engineer to design and operate large-scale GPU clusters across on-prem, cloud, and hybrid environments. You will implement automated tooling, improve performance, and ensure governance and cost efficient operations.

Travel 25-60% may be required; 5+ years with GPUs, Kubernetes, and automation is expected. This role is based in Massachusetts with competitive benefits and career growth opportunities.