AI Infra Operations Engineer: GPU Clusters & Automation

Accenture; New York (NY); On-site; USD 87,000 - 266,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Long-term disability

401(k)

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking a Senior AI Infrastructure Engineer to design, deploy, and optimize GPU-based clusters for AI workloads across on-premises, cloud, and hybrid environments. The role emphasizes scalable, secure, and cost-aware infrastructure with strong automation and governance in a global AI stack.

Travel may be required; 25%–60% depending on client needs. A Bachelor's degree or equivalent experience is required, with 5+ years in accelerated-computing infrastructure and hands-on experience

Qualifications

• Minimum of 5+ years designing, deploying, and managing accelerated-computing infrastructure across on-premises, cloud, and hybrid environments.
• Hands-on experience with GPUs, DPUs, CPUs, high-bandwidth networks, and AI storage architectures.
• 5+ years with cluster management, scheduling, orchestration, observability, and automation (Kubernetes, Slurm, Run:ai).
• 6 months hands-on with Claude Code, AI automation tools, Terraform, Ansible, Python, and Bash scripting.
• Bachelor's degree or equivalent work experience (minimum 12 years).

Responsibilities

• Design and implement accelerated-computing infrastructure solutions aligned to system architecture, deployment roadmaps, performance, scalability, resiliency, and governance requirements.
• Deploy, configure, and operate GPU-based clusters across bare-metal and containerized environments using workload schedulers and Kubernetes.
• Integrate infrastructure platforms with enterprise systems, data platforms, security frameworks, service-management processes, and governance controls.
• Develop and maintain automation workflows for provisioning, configuration management, validation, capacity planning, monitoring, incident management, and remediation.
• Establish repeatable operational processes for cluster provisioning, configuration management, patching, monitoring, and lifecycle management.
• Benchmark and validate GPU, compute, storage and network; diagnose performance issues across multi-node workloads.
• Maintain architecture diagrams, runbooks, and support documentation.
• Provide guidance and optimization for GPU clusters supporting AI training, inference, HPC, and multi-node simulations.

Skills

Kubernetes

Slurm

Run:ai

GPU clusters

Python

Bash scripting

Terraform

Ansible

NVIDIA BCM/NGC/NCCL

NVIDIA CUDA-X

Education

Bachelor's degree

Tools

BCM

NGC

NCCL

CUDA-X

NVAIE

Dynamo

Job description

Accenture is seeking a Senior AI Infrastructure Engineer to design, deploy, and optimize GPU-based clusters for AI workloads across on-premises, cloud, and hybrid environments. The role emphasizes scalable, secure, and cost-aware infrastructure with strong automation and governance in a global AI stack.

Travel may be required; 25%–60% depending on client needs. A Bachelor's degree or equivalent experience is required, with 5+ years in accelerated-computing infrastructure and hands-on experience