AI Infrastructure Engineer: GPU-HPC Clusters & MLOps

Freelio; Northern (KY); Hybrid; USD 90,000 - 230,000; Full time

Job summary

Accenture is seeking a senior AI infrastructure engineer to design and deploy accelerated computing environments across on-prem, cloud, and hybrid settings. You will configure GPU clusters, integrate with data pipelines, and ensure governance and observability.

The role emphasizes production serving, model endpoints, and agentic AI workflows, with travel as required. Strong PKI and security practices are essential.

Qualifications

• Minimum of 5+ years designing and deploying AI infrastructure across on-premises, cloud, and hybrid environments.
• Experience with GPUs, DPUs, LPUs, CPUs and high-speed interconnects; familiarity with InfiniBand or Ethernet networks.
• Proficient in Kubernetes, Slurm, Run:ai; scripting in Python; IaC with Terraform/Ansible.

Responsibilities

• Design and implement AI infrastructure and accelerated computing solutions.
• Deploy GPU/CPU clusters across bare-metal and containerized environments with orchestration.
• Develop and maintain documentation and runbooks; provide troubleshooting and optimization guidance.

Skills

Kubernetes

Slurm

Run:ai

Python

Terraform

Education

Bachelor's degree or equivalent

Tools

NVIDIA CUDA

TensorRT-LLM

NCCL

MLPerf

Job description

Accenture is seeking a senior AI infrastructure engineer to design and deploy accelerated computing environments across on-prem, cloud, and hybrid settings. You will configure GPU clusters, integrate with data pipelines, and ensure governance and observability.

The role emphasizes production serving, model endpoints, and agentic AI workflows, with travel as required. Strong PKI and security practices are essential.