Senior Solutions Architect, Cloud Infrastructure and DevOps

About the Role

NVIDIA is seeking a Senior Solutions Architect, Cloud Infrastructure and DevOps to join its NVIDIA Infrastructure Specialist Team. Academic and commercial groups worldwide are leveraging NVIDIA products to redefine deep learning, data analytics, and power state-of-the-art data centers. This role offers the opportunity to be involved with the team developing many of the largest and fastest AI/HPC systems globally. We are looking for an individual capable of thriving in a dynamic, customer-focused environment that demands exceptional interpersonal skills. You will interact with customers, partners, and various internal departments to analyze, define, and implement large-scale Networking projects. The scope of these efforts encompasses Networking, System Building, Kubernetes-based platforms, and Automation, while serving as the primary technical interface to the customer.

What You'll Be Doing

• Maintain large-scale computational and AI infrastructure, with a strong focus on monitoring, logging, and workload orchestration (Kubernetes and Linux job schedulers).
• Perform end-to-end troubleshooting across the entire stack, from bare metal and operating system, through the software stack, container platform, networking, and storage.
• Optimize scalable, production-ready Kubernetes-based container platforms integrated with enterprise-grade networking and storage solutions.
• Serve as a key technical resource, developing, refining, and documenting standard methodologies and operational guidelines for internal teams.
• Support Research & Development activities and engage in Proof-of-Concept (POCs) and Proof-of-Value (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.
• Become the 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

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, combined with 8+ years of professional experience in managing scalable cloud environments and automation engineering roles.
• Cloud & HPC Expertise: Proven understanding of networking fundamentals (TCP/IP stack), data center architectures, and hands-on experience managing HPC/AI clusters, including deployment, optimization, and troubleshooting.
• Kubernetes & AI/ML Workloads: Extensive experience with Kubernetes for container orchestration, resource scheduling, scaling, and integration with HPC environments.
• Hardware & Software Knowledge: Familiarity with HPC and AI technologies (CPUs, GPUs, high-speed interconnects) and supporting software stacks.
• Linux & Storage Systems: Deep knowledge of Linux (RedHat/CentOS, Ubuntu), OS-level security, and protocols (TCP, DHCP, DNS). Experience with storage solutions such as Lustre, GPFS, ZFS, XFS, and emerging Kubernetes storage technologies.
• 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.

Ways To Stand Out From The Crowd

• Knowledge of CI/CD pipelines for software deployment and automation.
• Solid hands-on knowledge of Kubernetes and container-based microservices architectures.
• Experience with GPU-focused hardware and software (e.g., NVIDIA DGX, CUDA, GPU Operator).
• Background with RDMA-based fabrics (InfiniBand or RoCE) in HPC or AI environments.

Key skills/competency

• Cloud Infrastructure
• DevOps
• Kubernetes
• HPC/AI Systems
• Networking
• Linux Administration
• Automation (Python, Bash, Ansible, Terraform)
• Observability (Grafana, Prometheus)
• Troubleshooting
• Customer Engagement