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Senior Software Engineer, Cloud-Native Stack – CSP Engagements

NVIDIA· Engineer, Sys SW
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US, CA, Santa Clara, US, TX, Austin, Remote, US, WA, Redmond, US, WA, Seattle$184k - $287.5k + equityFull-timePosted 7mo ago

About the role

Senior software engineer focused on the cloud-native stack for CSP engagements in AI/ML datacenters, debugging and prototyping Kubernetes/Slurm-based solutions for multi-rack, multi-tenant GPU environments.

Responsibilities

  • Perform deep-dive debugging of multi-rack, multi-tenant clusters: scheduler behavior, container runtime issues, device-plugin crashes, RDMA/IB fabric anomalies, etc.
  • Gather customer requirements and prototype feature extensions for Kubernetes operators, Slurm plugins, and custom micro-services that expose new GPU capabilities.
  • Drive joint architecture reviews and whiteboard sessions with CSP and internal platform teams; convert findings into RFCs and upstream pull requests.
  • Create reproducible testbeds (Helm/Ansible/Terraform) that mirror customer environments; automate validation and benchmark suites.
  • Deliver technical collateral-design docs, how-to guides, demo scripts—and present at customer on-sites, KubeCon, and SlurmUG.
  • Collaborate with AE, FAE, and Solution Architect teams to deliver integrated customer solutions and technical documentation.

Qualifications

  • Strong source-level expertise in Kubernetes internals (scheduler, CRI/CNI/CSI, operators) and Slurm (federation, power-save, plugins).
  • Hands-on experience integrating next-gen GPUs (Blackwell/GB200/GB300) or comparable accelerators into containerized clusters.
  • Proven track record debugging large-scale, cloud-native stacks across networking (RDMA/RoCE), storage, and control planes.
  • Customer-facing engineering or solutions-architect background: requirements gathering, PoC ownership, roadmap influence.
  • Familiarity with CI/CD (GitHub Actions, Tekton), observability (Prometheus, OpenTelemetry), and infrastructure-as-code.
  • Excellent communication—ability to switch between deep technical detail and high-level business impact.
  • 10+ years of professional software development experience in distributed systems (Go, Rust, C/C++ or Python for tooling).
  • BS or MS (or equivalent) in Computer Engineering, Computer Science, or related field.

Skills

Required:Kubernetes internalsSlurmGPU integrationCI/CDObservabilityInfrastructure as code

Benefits

  • equity
  • benefits (as described in NVIDIA benefits page)
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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