AI & HPC Infrastructure Engineer

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

## JobbeskrivelseWe Are:The Global AI Infrastructure team is at the center of enabling infrastructure reinvention for the next era of digital solutions powered by AI, accelerated computing, and high-performance workloads. We bring together deep technical expertise across cloud, on-premises, and hybrid environments to design, build, and operate advanced infrastructure that powers AI platforms, GPU-accelerated workloads, large-scale models, simulations, and emerging agentic AI solutions at scale. Our solutions enable some of our most strategic and mission-critical clients to unlock new levels of performance, efficiency, governance, and innovation. Our remit spans the full lifecycle-from strategy and architecture through implementation and operations-driving modernization across the entire infrastructure stack. We collaborate across the ecosystem to harness emerging technologies, fuel growth, and transform industries. In this rapidly growing market, our team is leading the way in shaping how enterprises leverage AI infrastructure to drive breakthrough innovation and reimagine what is possible.Key Responsibilities:•Design and implement AI infrastructure and accelerated computing solutions, aligning system architecture and deployment roadmaps to industry-specific performance, scalability, resiliency, and governance needs•Deploy, configure, and manage XPU-based clusters (GPU, DPU, LPU, CPU) across bare-metal and containerized environments using workload schedulers (Slurm, Run:ai), Kubernetes orchestration, and container platforms to deliver scalable AI infrastructure services including Bare-Metal-aaS, GPUaaS, AIaaS, Token-aaS, model serving, and agentic AI frameworks•Integrate AI infrastructure platforms with existing IT systems, data pipelines, security frameworks, model-serving endpoints, and enterprise governance controls•Design and implement agentic AI infrastructure by integrating platform services, model endpoints, tool and function calling, retrieval patterns, and workflow orchestration with observability, identity, and policy controls through secure, deterministic APIs to support governed enterprise use cases•Build and integrate MCP servers, tools, connectors, and adapters that allows agents to monitor, troubleshoot, and tune infrastructure to ensure high availability, low-latency networking, and workload resiliency•Architect and deploy with NVIDIA platform tools including Base Command Manager (BCM), NGC, NCCL, NVLink, and CUDA along with LLM inference engines (TensorRT-LLM), production serving frameworks (vLLM, SGLang), inference orchestration (Triton Inference Server, NVIDIA Dynamo, llm-d), and GPU benchmarking and validation tools (MLPerf, NCCL tests, fio, iperf) to deploy, tune, profile, and validate AI cluster performance across compute and networking layers including multi-node training and inference workloads•Develop and maintain documentation including architecture diagrams, configuration baselines, and operational runbooks•Provide technical guidance, troubleshooting, and optimization across AI workloads including large-scale training, inference, multi-node simulations, and agentic pipelines while leveraging digital twins to validate infrastructure and drive performance, scalability, energy efficiency, and token cost optimizationTravel may be required for this role. The amount of travel will vary from 25% to 100% depending on business need and client requirements.Required Skills and Qualifications:• Minimum of 5+ years of experience designing, deploying, and managing AI infrastructure and accelerated computing environments across on-premises, cloud, and hybrid environments for hyperscaler, neocloud, large enterprise, Telco/Mobile, Financial Services, Life Sciences, Manufacturing, and/or Retail clients.• Minimum of 5+ years of hands-on experience with accelerated computing platforms, including GPUs, DPUs, LPUs, CPUs, high-speed interconnects such as InfiniBand or Ethernet, data center networking such as SONiC, and AI storage architectures including NVMe, NVMe-oF, parallel file systems, VAST, Weka, or DDN.• Minimum of 5+ years of experience with cluster management, workload scheduling, orchestration, observability, and infrastructure automation using platforms and tools such as Kubernetes, Slurm, Run:ai, AWS, Azure, GCP, VMware, Nutanix, Python, Terraform, and Ansible.• 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:• 2+ years of experience implementing MLOps, LLMOps, agentic AI, and DevSecOps frameworks to enable secure, automated, governed, and reproducible AI workflows.• 2+ years of experience developing APIs, integration services, automation workflows, or platform services using Python and modern API patterns such as REST, OpenAPI, JSON/YAML schemas, webhooks, and event-driven integrations.• Experience designing and implementing agentic AI infrastructure, including LLM inference, tool/function calling, retrieval-augmented generation (RAG), agent orchestration, secure API integration, policy-based governance, and deterministic platform APIs.• Experience building and integrating MCP servers, tools, connectors, and adapters that allow agents to monitor, troubleshoot, and tune infrastructure for high availability, low-latency networking, workload resiliency, and intelligent observability.• Experience using NVIDIA platform tools including Base Command Manager (BCM), NGC, NCCL, NVLink, CUDA, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, llm-d, vLLM, SGLang, MLPerf, NCCL tests, fio, and iperf to deploy, tune, profile, and validate AI cluster performance.• Experience managing the deployment of 1,000+ GPU clusters for AI, HPC, and agentic AI workloads with infrastructure services enabled.• Design and build experience in AI Cloud platforms from CoreWeave, Nebius, and other specialty cloud providers.• Knowledge of machine learning and AI frameworks such as TensorFlow, PyTorch, JAX, Jupyter notebooks, and Google Colab environments.• Industry certifications in NVIDIA infrastructure, public cloud providers, data science, 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 10/15/2026.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 | AccentureRole Location Annual Salary RangeCalifornia $94,400 to $266,300Colorado $94,400 to $230,000Connecticut $94,400 to $230,000District of Columbia $100,500 to $245,000Illinois $87,400 to $230,000Maine $80,400 to $196,000Maryland $94,400 to $230,000Massachusetts $94,400 to $245,000Minnesota $94,400 to $230,000New York $87,400 to $266,300New Jersey $100,500 to $266,300Ohio $87,400 to $213,000Virginia $87,400 to $245,000Washington $100,500 to $245,000About AccentureAccenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. 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Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.For details, view a copy of the Accenture Equal Opportunity StatementAccenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.Accenture is committed to providing veteran employment opportunities to our service men and women.Other Employment Statements Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment. 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