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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Network Visibility Platform - DGX Cloud - **Company:** NVIDIA Corporation - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $168,000.0 - $270,250.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Data Centers, Graph Database, Network Topologies, InfiniBand, Python (Programming Language), Network Architecture, Networking Basics, Network Model, Routing, Open Source Technology, Remote Direct Memory Access, Prometheus, Data Streaming, TypeScript, Computer Network Operations, ReactJS, Grafana, Event Driven Architecture, Kubernetes, Front End Software Development - **Published:** September 25, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Software-Engineer--Network-Visibility-Platform---DGX-Cloud_JR2026403 ## About the Role * Bachelor's degree or equivalent experience, plus 10+ years of relevant industry experience * Record of architecting and operating large-scale software or infrastructure platforms, with strong proficiency in Python, Go, or a comparable systems language * Deep expertise in one area-with breadth across the others: network topology and sources of truth, telemetry and active measurement, or observability products * Strong data center and backbone networking fundamentals across physical connectivity, routing, overlays, services, and customer-visible failures * Hands-on experience across an observability stack such as Prometheus, Grafana, and OpenTelemetry, including active or synthetic monitoring and containerized deployment on Kubernetes * Experience with large-scale graph, relational, time-series, streaming, API, or event-driven systems that reconcile multiple sources * Technical leadership across teams, with strong product and operational judgment and clear tradeoffs among performance, resiliency, usability, and cost Ways to stand out from the crowd: * Led a network visibility or infrastructure intelligence platform spanning thousands of devices or hosts * Experience with AI or HPC networks, including RDMA, RoCE over Spectrum-X, or InfiniBand * Experience with network sources of truth such as NetBox or Nautobot, streaming telemetry (gRPC/gNMI), graph databases, or front-end development in TypeScript and React * SRE or network operations experience, plus a record of setting standards, making build-versus-buy decisions, or contributing to open source ## Description As a Senior Software Engineer on NVIDIA's Global Network Visibility (GNV) team within NVIDIA's Global Network Infrastructure (GNI) organization, you will lead the platform that turns network topology, configuration, telemetry, and direct measurement into trusted, self-service insight. Your work will help teams understand network health and customer impact, accelerate incident triage, and bring AI, storage, backbone, and edge infrastructure online with confidence. You will set direction across authoritative network data, scalable measurement, and customer-facing visibility products. You will define durable interfaces, lead cross-domain decisions, and guide build-versus-buy choices. Success means the platform is credible, adopted, and trusted. What you'll be doing: * Set the architecture for a unified platform spanning topology, configuration, telemetry, active measurement, change intelligence, and self-service experiences * Build an authoritative network model connecting physical topology, logical overlays, configurations, and service dependencies across systems of record, and use it to catch physical and logical configuration errors during cluster bring-up * Define a telemetry & measurement strategy combining reachability tests, streaming signals, traffic & capacity data, and change & maintenance events * Deliver intuitive health, path, blast-radius, and self-service exploration products that help customers answer network questions independently * Establish interfaces, data contracts, quality standards, and operating mechanisms that let teams contribute without fragmenting the experience * Drive cross-functional roadmaps; make clear tradeoffs among speed, cost, reliability, and maintainability; and mentor engineers through critical designs ## Related Videos - [Your Next AI Needs 10,000 GPUs. 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