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 08/15/2026.
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 | Accenture
Role Location Annual Salary Range
California $94,400 to $266,300
Cleveland $87,400 to $213,000
Colorado $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
Virginia $87,400 to $245,000
Washington $100,500 to $245,000
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