Senior Solutions Architect, Cloud Infrastructure – DevOps

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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 solving 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 partners. • Support Research & 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 as the technical leader for assigned customer accounts, providing strategic guidance on DevOps and platform architecture and influencing long-term infrastructure and operations decisions.

🎯 Requirements

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields (or equivalent experience) with 8+ years of professional experience in leading scalable cloud environments and automation engineering roles. • Shown understanding of networking fundamentals, data center architectures, and hands-on experience leading HPC/AI clusters, including deployment, optimization, and solving. • Validated hands-on experience deploying, configuring, and optimizing NVIDIA GPU-accelerated infrastructure, including driver management, CUDA toolkit integration, and GPU workload profiling. • Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with GPU-accelerated and HPC environments. • Strong familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks. • Deep knowledge of Linux (RedHat, Ubuntu), OS-level security, and protocols. • Experience with storage solutions such as Lustre, GPFS, ZFS, XFS, and emerging Kubernetes storage technologies. • 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. • Strong background in crafting scalable solutions and providing consultative support to customers, including leading architectural reviews and speaking publicly to executive partners.