AI Infrastructure Engineer: GPU Clusters & Automation

Accenture; San Francisco (CA); On-site; USD 94,000 - 266,000; Full time

Benefits offered by this job

Medical benefits

Dental & Vision insurance

Life insurance

401(k) plan

Paid holidays

Paid time off

Job summary

Accenture is seeking a seasoned engineer for the Global AI Infrastructure team in California to design and operate GPU-driven clusters and accelerated-computing platforms. You will work across on‑prem, cloud, and hybrid environments to ensure high performance, scalable AI workloads and robust governance.

The ideal candidate has 5+ years in accelerated infrastructure, Kubernetes and automation toolchains, with hands-on GPU/DPUs and a strong scripting background.

Qualifications

• Minimum 5+ years of experience designing, deploying, and managing accelerated-computing infrastructure across on-premises, cloud, and hybrid environments.
• Hands-on experience with GPUs, DPUs, and CPUs, high-bandwidth networks, and AI storage architectures.
• 5+ years of experience with cluster management, workload 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 (12 years) or 6 years for Associate’s degree.

Responsibilities

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

Skills

GPU clusters

Kubernetes

Terraform

Python

Bash scripting

Education

Bachelor's degree or equivalent

Tools

Kubernetes

Slurm

Run:ai

Ansible

REST APIs

Job description

Accenture is seeking a seasoned engineer for the Global AI Infrastructure team in California to design and operate GPU-driven clusters and accelerated-computing platforms. You will work across on‑prem, cloud, and hybrid environments to ensure high performance, scalable AI workloads and robust governance.

The ideal candidate has 5+ years in accelerated infrastructure, Kubernetes and automation toolchains, with hands-on GPU/DPUs and a strong scripting background.