Observability Platform Engineer

About Nscale

Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale simplifies AI development while enabling superior results, supporting strategic business outcomes such as cost management, rapid innovation, and environmental responsibility.

We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you'll build trust through openness and transparency while contributing to the technology that powers the future.

About the Role

As a Staff Observability Platform Engineer, you'll play a critical role in building and evolving Nscale's observability platform, enabling deep visibility into GPU clusters, AI workloads, and the infrastructure that powers them.

You view observability as a product, not simply a collection of tools. You'll help define and implement scalable, reliable observability solutions that empower engineering teams to understand system behavior, diagnose issues quickly, and operate complex distributed systems with confidence.

You'll combine technical leadership with hands-on engineering, partnering across SRE, infrastructure, platform, and AI/ML teams to improve reliability, operational efficiency, and developer experience. You'll influence architectural decisions, establish engineering best practices, and help drive the evolution of observability capabilities across the organization.

This is a role for someone who enjoys solving difficult infrastructure problems, building platforms that scale, and helping engineering teams succeed through better visibility and operational insight.

What You'll Do

• Design, build, and evolve observability platforms across metrics, logs, traces, alerting, and telemetry pipelines.

• Lead the implementation of scalable observability solutions that support Nscale's growing GPU and AI infrastructure.

• Partner with SRE, infrastructure, platform, and AI/ML teams to ensure observability is embedded throughout the software and infrastructure lifecycle.

• Drive improvements in monitoring coverage, alert quality, service health visibility, and incident response effectiveness.

• Develop standards, frameworks, and reusable patterns that simplify observability adoption across engineering teams.

• Identify reliability risks and operational blind spots, helping teams proactively address them before they impact customers.

• Contribute to architectural decisions around telemetry collection, storage, retention, cardinality management, and performance optimization.