Senior Software Engineer, Cloud-Native Stack – CSP Engagements

NVIDIA; Durham (NC); On-site; USD 184,000 - 287,500; Full time

Benefits offered by this job

Equity

Diverse work environment

Job summary

NVIDIA is seeking a Senior Software Engineer for the CSP Engagements team in Durham, North Carolina. The role will focus on developing advanced AI/ML datacenters using NVIDIA GPUs. Responsibilities include debugging complex multi-rack clusters and collaborating with clients to enhance cloud-native products.

Ideal candidates will have 10+ years of experience in distributed systems, a strong background in Kubernetes internals, and excellent communication skills. A competitive salary range is offered, alongside equity and benefits.

Qualifications

• Strong source-level expertise in Kubernetes internals and Slurm.
• Hands-on experience integrating next-gen GPUs into containerized clusters.
• Proven track record debugging large-scale cloud-native stacks.
• Customer-facing engineering or solutions-architect background.
• Familiarity with CI/CD, observability, and infrastructure-as-code.
• Excellent communication skills.
• 10+ years of professional software development experience.

Responsibilities

• Perform deep-dive debugging of multi-rack, multi-tenant clusters.
• Gather customer requirements and prototype feature extensions.
• Drive architecture reviews and convert findings into RFCs.
• Create reproducible testbeds for customer environments.
• Deliver technical collateral and present at events.
• Collaborate with AE, FAE, and Solution Architect teams.

Skills

Kubernetes internals

Slurm

GPU integration

Cloud-native stacks

CI/CD

Observability

Communication skills

Education

BS or MS in Computer Engineering, Computer Science or related field

Tools

Go

Rust

C/C++

Python

Helm

Ansible

Terraform

Job description

We are developing advanced multi‑rack, multi‑tenant AI/ML datacenters with NVIDIA GB200, and upcoming GB300 GPUs. NVIDIA seeks a Senior Software Engineer for our CSP (Cloud Service Provider) Engagements team to focus on the cloud‑native stack for datacenter products like GB200. In this role, you will define customer workflows, prototype stack enhancements, and debug the toughest Kubernetes + Slurm issues in multi‑rack, multi‑tenant AI datacenters. You'll tackle complex scheduling challenges across racks, tenants, and clouds as part of the CSP engagements team.

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—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.

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 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse 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.