AI Infra Engineer: GPU-Accelerated HPC & Agentic AI

Accenture; Carmel (IN); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) with matching

Paid holidays and PTO

Job summary

Accenture is seeking a seasoned AI Infrastructure professional to design, deploy, and manage scalable AI infrastructure across on-prem, cloud, and hybrid environments. You will work with GPUs, DPUs, LPUs, and high-speed networks, ensuring secure, governed, and efficient platform operations.

The role emphasizes collaboration, tooling with Kubernetes and Slurm, and integration with enterprise data ecosystems to enable large-scale AI workloads and agentic AI capabilities.

Qualifications

• Minimum of 5+ years designing, deploying, and managing AI infrastructure across on-prem, cloud, and hybrid environments.
• Experience with GPUs/DPUs/LPUs, InfiniBand Ethernet, and AI storage architectures.
• Proficient in Kubernetes, Slurm, Run:ai, Terraform, Ansible, Python.
• Bachelor's degree or equivalent work experience (min 12 years) or 6 years with Associate degree.

Responsibilities

• Design and implement AI infrastructure and accelerated computing solutions.
• Deploy, configure, and manage XPU-based clusters across bare-metal and containerized environments.
• Integrate AI infrastructure platforms with existing IT systems, security, and governance.
• Provide technical guidance, troubleshooting, and optimization for large-scale AI workloads.

Skills

AI infrastructure

Kubernetes

Python

Terraform

NVIDIA tools

Slurm

Run:AI

Docker

Terraform/Ansible

Education

Bachelor's degree or equivalent

Tools

Kubernetes

Slurm

Run:ai

NVIDIA CUDA/TensorRT

Triton Inference Server

Python

Terraform

Ansible

Job description

Accenture is seeking a seasoned AI Infrastructure professional to design, deploy, and manage scalable AI infrastructure across on-prem, cloud, and hybrid environments. You will work with GPUs, DPUs, LPUs, and high-speed networks, ensuring secure, governed, and efficient platform operations.

The role emphasizes collaboration, tooling with Kubernetes and Slurm, and integration with enterprise data ecosystems to enable large-scale AI workloads and agentic AI capabilities.