Senior Staff SRE – Compute Platform
Nvidia
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Preparing for this interview
Interviews for platform roles keep coming back to Observability, Python, AWS, Kubernetes. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with Observability? Tell me one thing you learned the hard way.
- 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?
- How do you keep secrets and access safe in your infrastructure?
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Practise the Senior Staff SRE – Compute Platform at Nvidia interview free →NVIDIA is seeking a Senior Staff SRE to build and operate reliable, scalable compute platforms that support global engineering workloads. This role spans Kubernetes, KubeVirt, bare-metal infrastructure, automation, observability, and AI-enabled operations. Join a team that solves complex infrastructure challenges, builds durable automation, and improves the reliability and operational experience of critical compute services. What you’ll be doing: Build, operate, and improve large-scale Kubernetes, KubeVirt, Linux, container, and bare-metal compute platforms, with a focus on performance, capacity, reliability, and operational scale. Lead bare-metal provisioning and lifecycle management in data centers, including PXE boot, DHCP, DNS, OS provisioning, hardware validation, and fleet automation. Develop automation, self-service capabilities, and observability solutions using APIs, Python or Go, Infrastructure as Code, configuration management, metrics, logs, traces, and service-health data. Define and operate SLOs, SLIs, error budgets, alerting, and incident-response practices; lead complex incident investigations, corrective actions, and blameless postmortems. Partner with infrastructure, security, hardware, data-center, and application teams to deliver global platform initiatives, and participate in an on-call rotation. What we need to see: BS in Computer Science, Engineering, a related technical field, or equivalent experience, plus 10+ years operating production infrastructure or platform services. Strong expertise in Kubernetes administration, KubeVirt, Docker, containerization, microservices, Linux systems, and resolving distributed-system challenges. Experience deploying and operating bare-metal infrastructure in a data-center environment, including provisioning, networking, operating-system lifecycle management, and hardware automation. Proficiency in Python, Go, or a comparable programming language, with experience building RESTful services and integrating infrastructure APIs. Experience with Infrastructure as Code and automation tools such as Terraform, Ansible, Chef, or Puppet, along with a solid understanding of TCP/IP networking and infrastructure security. Strong SRE and observability experience, including SLIs, SLOs, error budgets, incident management, monitoring, logging, tracing, and tools such as OpenTelemetry, Prometheus, Grafana, ELK Stack, or Splunk. Clear written and interpersonal communication skills, with a record of delivering practical, scalable solutions to complex technical problems. Ways to stand out from the crowd: Experience operating HPC, AI, GPU-accelerated, or general-purpose bare-metal compute infrastructure, including GPU-enabled Kubernetes or KubeVirt clusters. Expertise with VMware vSphere, Red Hat OpenShift, KVM, Firecracker, OpenStack, or Nutanix AHV. Experience applying generative AI or agentic workflows to improve infrastructure diagnostics, reduce operational toil, and accelerate incident resolution. Experience building secure, integrated operational platforms using APIs, RBAC, service accounts, secrets management, audit controls, workflow orchestration, and infrastructure or incident-management systems. Demonstrated delivery of complex, high-impact infrastructure projects.
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Listed on workday · posted 2026-09-28. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.