Senior Site Reliability Engineer

Job Requisition ID

JR2023915

Job Category

Engineering

Time Type

Full time

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are seeking a Staff DB SRE to build the runtime foundation for NVIDIA’s enterprise AI platforms — with a strong emphasis on database infrastructure at scale. This role blends large-scale database transformation with the building and development of GPU-accelerated platforms. You'll develop the software systems, automation frameworks, and high-performance database services that power NVIDIA’s AI workloads at scale.

What You'll Be Doing

• Design and operate highly available database clusters (MySQL, MSSQL, Oracle) with automated replication, failover, point-in-time recovery, and disaster-recovery strategies at enterprise scale.
• Drive database performance engineering — own query optimization, indexing strategies, connection pooling, lock-contention analysis, and storage-engine tuning for production systems handling millions of transactions.
• Build self-service database lifecycle automation — from one-click cluster provisioning and schema migrations to zero-downtime upgrades, blue-green deployments, and automated capacity scaling.
• Bridge relational and AI-native data infrastructure — extend traditional database expertise into vector search, GPU-accelerated query engines, and hybrid data platforms that serve both classic workloads and AI applications.
• Compose and build software platforms that transform legacy database systems into modern and scalable architectures.
• Run vector & graph database services and query engines to handle AI/ML data workloads with ultra-low latency.
• Build automation frameworks for provisioning, schema evolution, scaling, and failover integrated directly into CI/CD workflows.
• Build developer-focused tooling for monitoring, profiling, and debugging database performance in real time.
• Contribute to architecture, coding standards, and guidelines for long-term platform evolution.
• Participate in on-call rotations to ensure flawless operation of critical database services.
  
  

• BS, MS, or PhD in Computer Science, Engineering, or a related field—or equivalent experience.
• 8+ years of Database engineering experience with deep expertise in database systems or distributed data platforms
• Deep hands-on expertise with one or more major relational database engines (like Oracle, MySQL, MSSQL) — including replication topologies, backup/restore strategies, and high-availability architecture.
• Proven background in query optimization, data partitioning, and large-scale performance tuning.
• Experience building or operating managed database services or internal Database-as-a-Service platforms — automating provisioning, monitoring, patching, and failover for database fleets at scale.
• Strong programming skills in Python, Go, with a track record of building production-grade systems.
• Demonstrable experience crafting high-performance, high-availability relational database services.
• Experience with container orchestration (Kubernetes) and cloud-native database deployment patterns.
• Hands-on experience establishing DevOps guidelines, e.g., CI/CD, monitoring, alerting, SLAs, capacity forecasting, etc.
  
  

• Strong Kubernetes/Infrastructure as code and coding experience in addition to core DBA skills.
• Expertise in hybrid/multi-region database replication strategies for low-latency AI workloads.
• Demonstrable understanding of observability and performance profiling tools for complex data systems.
• You’ve built an internal Database-as-a-Service offering — engineers request a cluster and get a production-ready, fully monitored, backed-up database without filing a ticket.
• Hands-on experience with database migration tooling, schema evolution pipelines, and zero-downtime upgrade strategies across heterogeneous database engines