Senior Software Engineer, Cloud-Native Stack – CSP Engagements

What You’ll Be Doing

• 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.

What We Need To See

• 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 skills: able 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 experience) in Computer Engineering, Computer Science, or related field.

Ways To Stand Out From The Crowd

• Upstream contributions to Kubernetes, Slurm, Volcano, or similar projects.
• Experience with GPU computing (CUDA), deep learning workloads.

Pay

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is $184,000 - $287,500 for Level 4, and $224,000 - $356,500 for Level 5. You will also be eligible for equity and benefits.

Schedule

NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and 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.