Join NVIDIA's Infrastructure team as a Senior System Software Engineer and contribute to the advanced AI and accelerated computing platforms powering our global engineering efforts. This role is pivotal in developing and maintaining highly scalable distributed services that enhance the efficiency of thousands of NVIDIA software engineers daily. We are seeking a seasoned full-stack engineer passionate about building and monitoring robust systems.

This position offers an opportunity to define system architecture, guide development, and influence critical engineering workflows. You will play a key role in ensuring scalability, reliability, and cost-effectiveness while meeting delivery timelines. Emphasis will be placed on leading reviews and promoting safe, incremental feature rollouts across multiple teams.

You will shape the strategy for CI/CD pipelines and release practices, significantly improving build, test, and deployment speed and quality. A core part of this role involves supporting the adoption of containerized services using Docker and Kubernetes, advocating for automation to minimize operational overhead.

Define the observability approach, encompassing monitoring, logging, alerting, and SLOs, to proactively detect issues, reduce alert fatigue, and expedite incident resolution. You will also lead root-cause analysis for complex production incidents and champion long-term reliability improvements. Furthermore, this role includes mentoring and developing engineers, elevating engineering standards, and fostering collaboration across diverse teams and time zones.

We are looking for candidates with a BS/MS in Computer Science, Engineering, or equivalent experience, coupled with over 5 years of experience in building and operating large-scale backend or distributed systems. Deep expertise in Java, including concurrency, performance tuning, and debugging, is essential.

Demonstrated experience in crafting, scaling, and managing highly available full-stack applications in production, including leading architectural changes, is required. Proficiency with Version Control Systems like Gitlab and Gerrit, a solid understanding of data structures, algorithms, and distributed system development, along with experience in relational databases (e.g., MySQL) and NoSQL stores (e.g., Elasticsearch, MongoDB) are necessary. Experience with Docker, Kubernetes, infrastructure automation tools (Ansible, Chef), and observability tools (Prometheus, Grafana, Kibana, Splunk) is also expected. Strong technical leadership, mentoring abilities, and excellent communication skills for cross-team collaboration are vital.