Senior Site Reliability Engineer -ai Infrastructure Operations

About Nscale

Nscale is the GPU cloud engineered for AI—purpose-built to deliver high-performance, cost-efficient infrastructure for AI-native startups and global enterprises. We enable organizations to accelerate innovation, reduce the complexity of AI development, and achieve meaningful business outcomes through scalable, sustainable compute.

Our culture is defined by ownership, accountability, and rapid innovation. We operate with urgency and transparency, and every team member contributes to building the infrastructure powering the future of AI.

The Opportunity

Nscale’s AI Infrastructure Operations team supports one of the most demanding AI platforms in the industry. We are looking for a Senior Site Reliability Engineer to help design, build, and operate reliable, scalable infrastructure across our GPU cloud.

This role is focused on hands-on engineering, system reliability, and operational excellence. You will work across software, systems, and infrastructure to improve performance, automate operations, and ensure platform stability at scale.

What You’ll Be Doing

• Design, build, and improve automation, tooling, and infrastructure systems supporting AI and HPC workloads
• Contribute to the development of control-plane systems and operational frameworks
• Define and implement SLOs, SLIs, and monitoring strategies to ensure system reliability
• Participate in incident response and root cause analysis, driving improvements to reduce recurrence
• Identify and address reliability and performance bottlenecks across systems
• Collaborate with Engineering, Network, and Fleet teams to improve system design and operational processes
• Drive improvements in availability, scalability, and operational efficiency
• Mentor junior engineers and contribute to a strong engineering and reliability culture

What You Bring

• 5–8+ years of experience in SRE, Systems Engineering, or Software Engineering in production environments
• Strong software engineering skills with experience building automation and infrastructure tooling
• Solid understanding of Linux systems, networking, and distributed systems
• Experience troubleshooting issues across infrastructure, OS, networking, and application layers
• Familiarity with monitoring, alerting, and observability tools
• Ability to balance reliability, performance, and delivery speed

Preferred Experience

• Experience with AI or HPC environments, including GPUs or high-performance systems
• Exposure to high-speed networking (InfiniBand/RDMA)
• Familiarity with Kubernetes, cloud platforms, or bare-metal environments
• Experience with observability systems in high-scale environments

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