We are looking for a Senior Software Solutions Engineer to support NVIDIA AI Enterprise customers and deployments across cloud and datacenter environments. This is a dual role: (1) Support, triage and resolve complex customer software issues end-to-end, and (2) build software features, automation, diagnostics, reproducible test cases, and deployment toolingâ€'to improve product readiness and scale support across enterprise environments.

You will work across compute and cloud-native technologies in CSP environments, including container platforms/orchestrators, enterprise system software, and GPU-accelerated AI frameworks and inference services used to run production AI workloads at scale. 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)

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

BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience)

- 5+ years system software development and troubleshooting experience, ideally with some customer facing
- Robust computer science fundamentals and programming/scripting skills (Python required Bash Go/C++ a plus) to automate investigations and build diagnostics/repro tools
- Strong troubleshooting fundamentals (networking, concurrency, OS concepts) and a structured approach to isolating issues across application, platform, and infrastructure layers
- Deep understanding of at least two of the following: data centers/servers, distributed systems, virtualization, deep learning frameworks, containers (Docker/Kubernetes), hybrid cloud (AWS/Azure/GCP), and CI/CD for reliable deployments
- Familiarity with GPU-accelerated AI/ML stacks and production model deployment/serving (e.g., Deep Linux knowledge and comfort troubleshooting in production Linux environments working knowledge of Windows is a plus
- Hands-on experience deploying and operating NVIDIA AI Enterprise components in production across on-prem or CSP environments

Hands-on experience using AI coding assistants/tools (e.g., Cursor, Claude Code, Codex, or similar) to accelerate debugging, automation, and test creation

Experience operating Kubernetes-based platforms in production (cluster operations, upgrades, control-plane/data-plane failure modes)

Strong performance debugging skills for GPU and cloud workloads (profiling, latency/throughput tuning) and familiarity with observability/tracing tools

📌 Senior Software Engineer - Solutions Engineering (Pune)
🏢 NVIDIA
📍 Pune