Nvidia Senior System Software Engineer Platform Operations 

United States, Texas 

206530800

What you’ll be doing:

• Architect, build, and evolve the scalable technology stack for global learner and instructor technical support.

• Lead the global operationalization of support systems, to ensure high availability, performance, and efficient resource utilization.

• Provide technical leadership and mentorship to a distributed operations team, driving excellence in the use of support technologies and processes.

• Collaborate cross-functionally to translate support insights and user feedback into systemic improvements to shared NVIDIA services, the DLI platform, and overall experience for enterprises, learners, and instructors.

What we need to see:

• Bachelor’s degree in Computer Science, a related technical field, or equivalent experience

• Over 6 years of DevOps experience optimizing, deploying and running containerized applications (Docker, Kubernetes) across AWS, Azure, and GCP, including hands-on work with EKS, AKS, and GKE.

• Proficient in Python and Linux shell scripting for automation, application development, system administration, and troubleshooting.

• Validated experience architecting, implementing, and managing cloud infrastructure using Terraform.

• Demonstrated ability as a meticulous problem-solver with strong analytical skills, capable of diagnosing and resolving complex technical challenges under pressure.

• Excellent communication, teamwork, and collaboration skills, with an ability to articulate technical concepts clearly to diverse audiences and lead technical responses during incidents.

Ways to stand out from the crowd:

• Proven experience designing and implementing event-driven architectures using pub/sub patterns with platforms like AWS SNS / SQS, Google Pub / Sub, or Azure Service Bus.

• Knowledge of generative AI architectures (LLMs, diffusion models) and concepts such as Retrieval Augmented Generation (RAG) and vector databases.

• Hands-on experience with the NVIDIA AI stack (NeMo, Triton Inference Server, TensorRT) for model development, serving, and optimization. Production experience with NVIDIA NIM is a strong plus.

• Experienced in building and running CI/CD pipelines (Jenkins, GitLab CI) and managed software development environments, applying SRE principles to automate, enhance reliability, and improve performance.

• Familiarity with Python-based Learning Management Systems (LMS) such as Open edX.