Senior Software Engineer
Nvidia
Nvidia is also hiring for this role in Israel, Raanana, Israel, Raanana, Israel, Tel Aviv, Israel, Tel Aviv.
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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.
- Tell me about a hard bug you tracked down. How did you find the cause?
- How do you decide what to test, and what does good code review look like to you?
- Describe a time a deadline forced a trade-off in quality. What did you choose and why?
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Practise the Senior Software Engineer at Nvidia interview free →We are seeking a Senior Software Engineer with strong infrastructure expertise to design, build, and operate the next generation of our enterprise Observability, Automation, and AI-driven Reliability Platform. This role will build highly scalable distributed systems and platform services spanning Storage, Compute, Network, VMware, OpenShift, and bare-metal infrastructure. The engineer will help transform infrastructure operations from reactive monitoring and manual remediation to proactive, predictive, and AI-driven autonomous operations. What You Will Be Doing: Design, build, and operate distributed software platforms for enterprise observability, telemetry, automation, and infrastructure reliability at large scale. Develop reusable platform services, APIs, automation frameworks, and control planes that enable self-service, reduce operational toil, and automate infrastructure operations across multiple engineering teams. Build scalable telemetry and event-processing systems spanning metrics, logs, traces, events, topology, and alerts, with the performance and efficiency to process billions of infrastructure signals. Build intelligent and AI-native reliability capabilities, including agentic workflows for anomaly detection, forecasting, root-cause analysis, automated debugging, and closed-loop remediation. Drive technical architecture and engineering direction across Storage, Compute, Network, and Platform domains, solving complex and ambiguous problems that span multiple teams. Engineer for production at scale, with strong focus on software quality, scalability, security, performance, observability, maintainability, and operational readiness. Provide technical leadership and mentorship, influence engineering standards and architecture decisions, and deliver measurable improvements in reliability, MTTR, operational toil, engineering productivity, and infrastructure efficiency. What We Need To See: Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience, with 10+ years of software engineering, SRE, infrastructure, or distributed-systems experience and demonstrated technical leadership. Strong software engineering expertise in Go, Python, or equivalent languages, with experience designing and building production-grade distributed systems, platform services, APIs, and automation. Proven experience owning complex software/platform initiatives across multiple teams or infrastructure domains, from architecture and implementation through adoption and measurable impact. Deep understanding of distributed systems, event-driven architectures, microservices, APIs, and high-throughput data processing, including technologies such as Kafka, NATS, gRPC, or equivalent. Strong experience with modern observability and telemetry platforms, including OpenTelemetry, Prometheus, VictoriaMetrics, Vector, Loki, Grafana, ClickHouse, or equivalent technologies. Strong SRE and infrastructure knowledge across Kubernetes/OpenShift, VMware, bare-metal, storage, networking, and/or cloud environments, with experience using Terraform, Ansible, or equivalent automation technologies. Demonstrated ability to solve ambiguous problems, influence technical direction without direct authority, mentor engineers, establish engineering standards, and deliver measurable operational and business outcomes. Ways To Stand Out From The Crowd: Experience building software and reliability platforms for large-scale on-premises infrastructure, particularly Storage, Compute, Networking, VMware, and Kubernetes/OpenShift. Deep understanding of storage and infrastructure telemetry, including IOPS, latency, NVMe health, SAN/NAS topology, block/object storage, and infrastructure failure domains. Experience building self-healing systems, automated remediation, predictive operations, or autonomous SRE capabilities. Production experience applying Generative AI, AIOps, LLMs, or Agentic AI to incident triage, RCA, operational intelligence, debugging, or remediation; experience with LangChain, LlamaIndex, AutoGen, or equivalent is a plus. Experience building high-performance platform services using FastAPI, gRPC, or equivalent technologies.
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Listed on workday · posted 2026-10-13. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.