Senior Software Engineer, DGX Cloud Orchestration

NVIDIA is seeking a Senior Software Engineer to join its DGX Cloud team and build foundational systems for high-performance GPU infrastructure. The role focuses on designing scalable APIs, workflow automation, state management, and integrations that improve the reliability and efficiency of global cloud operations.

Responsibilities:

• Design and develop APIs to orchestrate and integrate operational workflows
• Build state management and workflow automation systems that streamline infrastructure lifecycle processes
• Collaborate across teams to codify business processes into scalable, self-measuring systems
• Develop extensible, schema-driven platforms for reducing manual toil and ensuring operational consistency
• Drive integrations with container orchestration tools like Kubernetes and observability systems such as Prometheus, OpenTelemetry, Grafana
• Optimize the reliability and efficiency of cloud operations through automated workflows and telemetry systems
• Lead and ship impactful technical projects, ensuring quality and scalability at every stage

Requirements:

• 8+ years of industry experience with a Bachelor's or Master's degree (or equivalent experience), or 2+ years with a PhD
• Expertise in designing, building, and operating services in a high reliability environment
• Proficiency in programming languages such as Go, Java, or Python
• Strong understanding of cloud infrastructure (AWS, GCP, Azure) and container technologies like Docker and Kubernetes
• Experience with high-scale distributed systems, including architectural patterns for APIs and data pipelines
• Outstanding communication and collaboration skills, with a focus on solving complex operational challenges
• A passion for automating manual processes and driving system efficiency
• A track record of designing workflow orchestration systems for large-scale infrastructure
• Proven experience in reducing operational inefficiencies through automation and integration
• Strong debugging and problem-solving skills in distributed environments
• Prior experience or strong familiarity with the operational aspects of the NVIDIA AI/ML software stack (e.g., CUDA, cuDNN, containerization)