Senior Solutions Architect, DevOps

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NVIDIA is looking for a Senior Cloud Infrastructure and DevOps Solutions Architect to join its NVIDIA Infrastructure Specialist Team. Academic and commercial organizations around the world are using NVIDIA products to redefine deep learning and data analytics, and to power next-generation data centers. Join theteambuilding and advising on many of the largest and fastest AI/HPC systems in the world! We are looking for someone who combines deep technical expertise with strong consulting and communication skills. This role will engage directly with customers, partners, and cross-functional teams to assess, architect, and guide the implementation of large-scale infrastructure projects. The scope spans system architecture, Kubernetes-based platforms, and automation—serving as both a trusted advisor and a hands-on technical leader. What You’ll Be Doing: Advise on and help maintain large-scale computational and AI infrastructure, including monitoring, logging, and workload orchestration (Kubernetes and Linux job schedulers). Provide consultative guidance and perform hands-on troubleshooting across the full stack—from bare metal and operating system, through the software stack, container platform, networking, and storage. Assess customer environments and recommend optimized, production-ready Kubernetes-based container platforms integrated with enterprise-grade networking and storage solutions. Serve as a key technical resource: develop, refine, and document standard methodologies and operational guidelines to be shared with internal teams and customer stakeholders. Support Development activities and engage in POCs/POVs to validate new features, architectures, and upgrade approaches. Create and deliver high-quality documentation, including runbooks, onboarding materials, and best-practice guides for customers and internal teams. Act asthe technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions. What We Need to See: Education Experience: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, with 5+ years of professional experience in managing scalable cloud environments and automation engineering roles. Cloud HPC Expertise: Proven understanding of networking fundamentals,data center architectures, and hands-on experience managing HPC/AI clusters, including deployment, optimization and troubleshooting. NVIDIA GPU Expertise: Demonstrated hands-on experience deploying, configuring, and optimizing NVIDIA GPU-accelerated infrastructure, including driver management, CUDA toolkit integration, and GPU workload profiling. Kubernetes AI/ML Workloads: Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with GPU-accelerated and HPC environments. Hardware Software Knowledge: Strong familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks. Linux Storage Systems: Deep knowledge of Linux (RedHat, Ubuntu), OS-level security, and protocols. Automation Observability: Proficiency in Python and Bash scripting, configuration management, and Infrastructure-as-Code tools (e.g., Ansible, Terraform). Experience with observability stacks (Grafana, Loki, Prometheus) for monitoring, logging, and building fault-tolerant systems. Solution Architecture Customer Engagement: Strong background in crafting scalable solutions and providing consultative support to customers, including leading architectural reviews and presenting to executive stakeholders. Ways to Stand Out from the Crowd: Knowledge of CI/CD pipelines for software deployment and automation. Solid hands-on knowledge of Kubernetes anditsoperatorsforGPU and Networkmanagement. PracticalexperiencewithSLURM, MPI,enrootandjobprovisioning ExperiencewithSWchangemanagementofclustersacrosscompute, network andstorage. Experience with NV

NVIDIA正在为其NVIDIA基础设施专家团队招聘一名高级云基础设施和DevOps解决方案架构师。全球的学术和商业机构正在使用NVIDIA产品重新定义深度学习和大数据分析，并为下一代数据中心提供动力。加入团队，参与构建全球许多最大、最快的AI/HPC系统并提供建议！我们正在寻找一位将深厚技术专长与强大的咨询和沟通能力相结合的人才。该角色将直接与客户、合作伙伴和跨职能团队互动，评估、架构设计并指导大型基础设施项目的实施。工作范围涵盖系统架构、基于Kubernetes的平台和自动化——既是值得信赖的顾问，也是亲力亲为的技术领导者。你将要做的工作：为大型计算和AI基础设施提供建议并帮助维护，包括监控、日志记录和工作负载编排（Kubernetes和Linux作业调度器）。提供咨询指导，并在全栈范围内进行 hands-on 故障排除——从裸机和操作系统，到软件栈、容器平台、网络和存储。评估客户环境，推荐经过优化的、生产就绪的基于Kubernetes的容器平台，并与企业级网络和存储解决方案集成。作为关键技术资源：开发、完善和记录标准方法论和操作指南，与内部团队和客户利益相关者共享。支持开发活动，参与POC/POV以验证新功能、架构和升级方法。创建并交付高质量文档，包括runbook、入门材料和面向客户及内部团队的最佳实践指南。担任指定客户账户的技术负责人，提供关于DevOps和平台架构的战略指导，并影响长期基础设施和运营决策。我们需要看到的：教育经验：计算机科学、电气/计算机工程、物理学、数学或相关领域的学士/硕士/博士学位，并具有5年以上管理可扩展云环境和自动化工程角色的专业经验。云HPC专长： proven 对网络基础知识、数据中心架构的理解，以及管理HPC/AI集群的 hands-on 经验，包括部署、优化和故障排除。NVIDIA GPU专长：展示部署、配置和优化NVIDIA GPU加速基础设施的 hands-on 经验，包括驱动管理、CUDA工具包集成和GPU工作负载分析。Kubernetes AI/ML工作负载：具有丰富的Kubernetes容器编排、资源调度、扩展以及与GPU加速和HPC环境集成的经验。硬件软件知识：熟悉HPC和AI技术（CPU、GPU、高速互连）及支持软件栈。Linux存储系统：深入了解Linux（RedHat、Ubuntu）、操作系统级安全和协议。自动化可观测性：精通Python和Bash脚本、配置管理和基础设施即代码工具（例如Ansible、Terraform）。具有可观测性栈（Grafana、Loki、Prometheus）用于监控、日志记录和构建容错系统的经验。解决方案架构与客户互动：在打造可扩展解决方案和为客户提供咨询支持方面具有强大背景，包括领导架构评审并向高管利益相关者展示。脱颖而出的方式：了解用于软件部署和自动化的CI/CD流水线。对Kubernetes及其用于GPU和网络管理的operator有扎实的 hands-on 知识。具有SLURM、MPI、enroot和作业配置的实践经验。具有跨计算、网络和存储的集群SW变更管理经验。具有NV经验

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