AI Infrastructure Operations Engineer

Accenture PLC; Arlington (VA); On-site; USD 87,000 - 245,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Life insurance

Long-term disability

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking an experienced AI Infrastructure Engineer to design and operate accelerated-computing infrastructure across on‑prem, cloud, and hybrid environments. You will deploy GPU clusters, orchestrate workloads with Kubernetes, and develop automation tools to improve reliability and scale.

Role requires 5+ years with GPUs and AI workloads, plus hands-on with Claude Code, Terraform, Ansible, Python and Bash. Location: Virginia, with travel as needed.

Qualifications

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

Responsibilities

• Design and implement accelerated-computing infrastructure solutions aligned to system architecture, deployment roadmaps, performance, scalability, resiliency, and governance.
• Deploy, configure, and operate GPU-based clusters across bare-metal and containerized environments, using schedulers and Kubernetes.
• Integrate infrastructure platforms with enterprise systems, data platforms, security frameworks, and governance controls.
• Develop and maintain reusable tools, scripts, self-service capabilities, and automation workflows for infrastructure operations.
• Establish repeatable operational processes for cluster provisioning, configuration management, patching, capacity planning, monitoring, and incident response.
• Perform and automate GPU, compute, storage, and network benchmarking and validation; diagnose performance issues.
• Develop architecture diagrams, configuration baselines, runbooks, and support documentation.
• Provide technical guidance, troubleshooting, and optimization for GPU clusters used for AI workloads.

Skills

GPU clusters

Kubernetes

Slurm

Run:ai

Terraform

Ansible

Python

Bash

AI automation

Education

Bachelor's degree or equivalent (12 years)

Tools

Kubernetes

Slurm

Run:ai

Terraform

Ansible

Python

Bash

NVIDIA BCM

Job description

Accenture is a global professional services company with leading capabilities in digital, cloud and security. Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and, Interactive, Technology, and Operations services, all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 738,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners, and communities. Visit us at www.accenture.com.

The Global AI Infrastructure team enables resilient, high-performance compute environments for strategic clients across cloud, on-premises, and hybrid deployments. We design, build, and operate large-scale GPU and accelerated-computing infrastructure that supports demanding AI training and inference, simulation, and high-performance compute workloads. Our work spans strategy, architecture, modernization, operations, governance, and continuous improvement across the infrastructure stack. We build reusable operational tools, automation workflows, and platform capabilities that make repeatable infrastructure tasks safer, faster, and more scalable. We collaborate across the technology ecosystem to harness new capabilities, drive business transformation, and deliver dependable services at scale.

Key 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 orchestration to support AI training, inference, and high-performance compute workloads.

• Integrate infrastructure platforms with enterprise systems, data platforms, security frameworks, service-management processes, and governance controls.

• Design, build, and maintain reusable tools, scripts, self-service capabilities, and automation workflows for infrastructure operations, including provisioning, configuration management, validation, capacity planning, monitoring, incident management, reporting, and recurring remediation.

• Establish repeatable operational processes for cluster provisioning, configuration management, patching, capacity planning, monitoring, incident response, and lifecycle management.

• Perform and automate GPU, compute, storage, and network benchmarking and validation; diagnose performance issues across multi-node AI training, inference, and distributed compute workloads.

• Develop and maintain architecture diagrams, configuration baselines, operational runbooks, and support documentation.

• Provide technical guidance, troubleshooting, and optimization for GPU clusters supporting AI training, inference, high-performance computing, and multi-node simulation workloads, with emphasis on availability, resiliency, scalability, energy efficiency, and cost management.

Travel may be required for this role. The amount of travel will vary from 25% to 60% depending on business need and client requirements.

Required Skills and Qualifications:

• Minimum of 5+ years of experience designing, deploying, and managing accelerated-computing infrastructure across on-premises, cloud, and hybrid environments for hyperscaler, neocloud, large enterprise, telecommunications, financial services, manufacturing, and/or retail clients.

• Minimum of 5+ years of hands-on experience with accelerated-computing platforms, including GPUs, DPUs, and CPUs, high-bandwidth network fabrics, and AI based storage architectures such as parallel file systems, NVMe-oF, etc.

• Minimum of 5+ years of experience with cluster management, workload scheduling, orchestration, observability, and infrastructure automation, including building operational tools and automation workflows with platforms such as Kubernetes, Slurm, Run:ai

• Minimum 6 months hands-on experience with Claude Code, AI automation tools, Terraform, Ansible, Python, and Bash scripting.

• Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Preferred Skills and Qualifications:

• Experience building AI infrastructure automation and operations tools, AgenticOps practices that enable secure, automated, governed, and reproducible platform operations.

• Experience developing reusable infrastructure code leveraging Python, platform services, and automation workflows using REST APIs, OpenAPI, JSON/YAML schemas, webhooks, and event-driven integrations.

• Experience operating large-scale GPU clusters, including capacity management, reliability engineering, change management, and performance validation for AI training, inference, HPC, and enterprise compute workloads.

• Experience using NVIDIA platform tools and libraries including Base Command Manager (BCM), NGC, NCCL, CUDA-X, NVAIE, Dynamo, benchmarking tools to deploy, tune, profile, and validate cluster performance for training and inference workloads.

• Experience managing deployments of 1,000+ GPU clusters with infrastructure services enabled for AI training, inference, high-performance, and enterprise compute environments.

• Design and build experience in running LLMs across AI Cloud platforms from CoreWeave, Nebius, and other specialty providers

• Knowledge of model deployments, tuning, and troubleshooting performance on AI Infrastructure

• Industry certifications in accelerated-computing infrastructure, public cloud providers, infrastructure automation, networking, or security are a plus.

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.

We anticipate this job posting will be posted until 10/13/2026.

Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here: U.S. Employee Benefits | Accenture (https://www.accenture.com/us-en/careers/local/benefits)

Role Location Annual Salary Range

California $94,400 to $266,300

Colorado $94,400 to $230,000

Connecticut $94,400 to $230,000

District of Columbia $100,500 to $245,000

Illinois $87,400 to $230,000

Maine $80,400 to $196,000

Maryland $94,400 to $230,000

Massachusetts $94,400 to $245,000

Minnesota $94,400 to $230,000

New York $87,400 to $266,300

New Jersey $100,500 to $266,300

Ohio $87,400 to $213,000

Virginia $87,400 to $245,000

Washington $100,500 to $245,000

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