Senior Site Reliability Engineer
Key Skills for This Role
Full Job Posting
What you'll be doing
Design and build production-grade automation frameworks, workflows, and data models that reduce manual operational work across provisioning, patching, image deployment, telemetry, and change management at large scale.
Engage in the complete lifecycle of services from deployment to incident response and long-term reliability improvement.
Develop software tools and platforms that integrate across data center systems: DCIM, alerting and observability stacks, compute/storage/networking control planes, and CI/CD pipelines.
Monitor and handle large-scale GPU and Kubernetes production environments; apply advanced observability tooling (Grafana, OpenTelemetry, PagerDuty) to proactively detect, prevent, and resolve incidents.
Build predictive and auto-healing systems by integrating incident analysis insights into automated break-fix and self-remediation solutions.
Participate in on-call rotations and practice sustainable incident response, including blameless postmortems and systematic root-cause-focused improvements.
Scale systems sustainably through code by pushing automation and self-service tools that improve reliability and engineering velocity.
What we need to see
- 6+ years of experience in SRE, production engineering, or infrastructure software engineering supporting large-scale, highly available environments.
- BS/BTech in Computer Science, Engineering, Physics, Mathematics, or equivalent experience.
- Strong software development skills with expertise in Python and/or Go; ability to design, build, and own production-quality tools and services, not just scripts.
- Deep knowledge of Kubernetes, Linux systems administration, and/or container technologies; experience handling large-scale bare-metal and cloud infrastructure.
- Confirmed experience building data center automation tools covering OS provisioning, image deployment, patching, packaging, and configuration management.
- Experience with CI/CD tooling and infrastructure-as-code workflows.
- Strong understanding of observability practices: metrics, logging, distributed tracing, and alerting design.
- Excellent communication skills with the ability to present technical work persuasively across multi-functional teams.
Ways to stand out from the crowd
- Built and delivered automation or reliability platforms at large scale. You measure impact by machines handled, incidents prevented, or hours of toil eliminated.
- You address production problems as an application developer would a build: consider the architecture initially, automate fully, and improve the system before moving on.
- You have a strong passion for investing in groundbreaking technology and environments where you learn new systems quickly.
- Confirmed ability to debug and optimize code, reduce system-level toil, and drive measurable reliability improvements through software.
- Experience with DCIM systems and asset database design and implementation.
- NVIDIA leads in Artificial Intelligence, High-Performance Computing, and Accelerated Computing. Our invention, the GPU, powers the next generation of AI infrastructure. We build systems to run this infrastructure globally. We need engineers to write software that keeps it reliable, efficient, and improving. If this work excites you, we want to hear from you.
- Known throughout the technology industry as a leading employer, NVIDIA delivers highly competitive salaries and an extensive benefits package. As you consider your future, explore what we can provide for you and those closest to you at www.nvidiabenefits.com/
- You will also be eligible for equity and benefits .
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
About NVIDIA
Computing platform company for AI and accelerated graphics.
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