Software Solutions Engineer

Responsibilities

• Develop and maintain product-facing features and deployment assets for AI Enterprise supportability (e.g., scripts, configuration guidance, Kubernetes manifests/Helm charts, and reproducible test cases)
• Develop and maintain Python-based tooling/automation (validators, log collectors, repro harnesses) to improve NVIDIA AI Enterprise deployment reliability across NGC and container orchestrators (e.g., Kubernetes)
• Contribute code-level fixes, patches, or pull requests (as appropriate) in collaboration with engineering to address customer-impacting issues and improve product readiness
• Support enterprise customers deploying NVIDIA AI Enterprise in datacenter and CSP environments, including Kubernetes-based and containerized production AI platforms
• Take ownership of customer issues from inception to resolution: reproduce in lab/cloud, collect diagnostics, provide mitigations, and partner with engineering on fixes
• Create high-quality bug reports and RFEs with clear repro steps, environment details (CSP/Kubernetes/GPU), impact analysis, and supporting artifacts
• Develop customer-facing and internal documentation (KBs, runbooks, deployment guidance) to improve time-to-value and reduce recurring issues
• Be on call one weekend per month in the event a customer has a Sev1 outage and requires engineering assistance
• What we need to see
• BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience)

Languages