Senior Cloud Infrastructure Automation Solutions Architect
Nvidia
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What infrastructure roles keep asking for: Python (32%), AWS (30%), Observability (26%), Kubernetes (25%), System design (25%), Linux (19%), Terraform (19%), CI/CD (17%) — counted across their open postings here.
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- Why do you want to join Nvidia?
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- Tell me about an outage you handled. What did you learn from it?
- How do you decide what to monitor, and what should wake someone up at night?
- How would you cut the cloud bill of a system without hurting it?
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Practise the Senior Cloud Infrastructure Automation Solutions Architect at Nvidia interview free →NVIDIA is looking for a Senior Cloud Infrastructure Automation 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 the team building 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 interpersonal skills. This role will engage directly with customers, partners, and teams across multiple functions 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: Infrastructure Management & Orchestration — Advise on and maintain large-scale AI/compute infrastructure, including monitoring, logging, and workload orchestration via Kubernetes and Linux job schedulers. Perform analysis, optimisation, and performance tuning of GPU-accelerated systems to ensure high availability and efficiency. Interconnect & Network Support — Support and validate high-speed interconnect fabrics (InfiniBand/Ethernet), including cabling verification, link-health checks, topology validation, and resolution of link-level issues such as transceiver faults and link flaps. Technical Leadership — Act as the technical lead for assigned accounts, driving strategic guidance on DevOps and platform architecture. Lead engagements to resolve issues, advocate for customer needs, and facilitate post-deployment reviews and incident retrospectives. Develop and present high-quality runbooks, onboarding materials, and useful guides for customers and internal teams. Offer actionable insights into NVIDIA’s infrastructure roadmap. What We Need to See: Education & Experience — BS/MS/PhD in Computer Science, Engineering, Physics, Mathematics or related fields, with 5+ years managing scalable cloud environments and automation engineering. Native or professional fluency in English. Cloud, HPC & Infrastructure — Experience in networking, data centre architectures, and hands-on management of HPC/AI clusters. Deep knowledge of Linux (RedHat, Ubuntu), OS-level security, and familiarity with HPC/AI hardware (CPUs, GPUs, high-speed interconnects) and supporting software stacks. Kubernetes, Automation & Observability — Experience in Kubernetes for container orchestration and GPU-accelerated workloads. Proficiency in Python/Bash scripting, automation tools (Ansible, Terraform), and observability stacks (Grafana, Loki, Prometheus) for monitoring and fault-tolerant systems. Solution Architecture & Customer Engagement — Background in crafting scalable solutions, providing consultative support, leading architectural reviews, and presenting to executive team members. Ways to Stand Out from the Crowd: DevOps & Observability — Proficiency in CI/CD pipelines for deployment automation, plus hands-on experience with monitoring/visualisation tools (Grafana, Prometheus, Loki) for alerting and fault-tolerant systems. Container & Orchestration Expertise — Experience with Kubernetes and container-based architectures, including familiarity with NVIDIA GPU and Network Operators. NVIDIA GPU Infrastructure — Hands-on experience with Base Command Manager (BCM) for provisioning and managing GPU clusters at scale, the CUDA toolkit, and RDMA-based fabrics (InfiniBand/RoCE) in HPC or AI environments. Language Skills — Knowledge of Mandarin or another Southeast Asian language to support regional engagement. NVIDIA is widely considered one of the most desirable employers in the technology sector. The company supports a diverse work environment and is proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. If you are creative, autonomous, and passionate about building the next generation of Agentic AI infrastructure, we want to hear from you!
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Listed on workday · posted 2026-10-03. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.