<h2>About Nscale</h2> <p>Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.</p> <p>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, where everyone is inspired to do their best work. If you join our team, you’ll be contributing to building the technology that powers the future.</p> <h2>About the Role</h2> <p>We’re hiring a <strong><strong class="textBold">Senior Cloud Native Platform Engineer</strong></strong> to build, operate, and improve the cloud-native platform foundations that support AI applications and services at scale.</p> <p>In this hands-on platform engineering role, you’ll work on shared <strong><strong class="textBold">Kubernetes-based platforms</strong></strong>, deployment patterns, observability foundations, infrastructure automation, and operational tooling that help internal teams run services safely and efficiently on <strong><strong class="textBold">GPU-backed infrastructure</strong></strong>. You’ll partner closely with software engineering, infrastructure, and SRE teams to ensure platform capabilities meet real developer and operational needs.</p> <p>This role is important to the reliability, scalability, and usability of Nscale’s platform. You’ll take ownership of significant platform components, deliver complex technical work independently, and raise the quality of operations and engineering through practical improvements, sound technical judgement, and mentoring.</p> <h2>What you'll be doing</h2> <h2>Platform Operations & Engineering</h2> <ul> <li value="1"><strong><strong class="textBold">Build</strong></strong> and improve shared cloud-native platform capabilities used by internal engineering teams to run AI applications and services.</li> <li value="2"><strong><strong class="textBold">Own</strong></strong> significant parts of the platform area, including Kubernetes cluster operations, workload runtime configuration, deployment workflows, observability foundations, or environment automation.</li> <li value="3"><strong><strong class="textBold">Improve</strong></strong> the reliability, scalability, and supportability of platform services through practical engineering and operational enhancements.</li> <li value="4"><strong><strong class="textBold">Develop</strong></strong> automation, tooling, and configuration that reduce manual effort, improve consistency, and make the platform easier to use and operate.</li> <li value="5"><strong><strong class="textBold">Apply</strong></strong> software engineering where it creates leverage, including scripts, services, CI/CD automation, operational tooling, and platform integrations.</li> </ul> <h2>Reliability, Operability & Automation</h2> <ul> <li value="1"><strong><strong class="textBold">Improve</strong></strong> incident prevention, detection, response, and recovery across the platform areas you support.</li> <li value="2"><strong><strong class="textBold">Build</strong></strong> and refine observability for platform services, including metrics, logs, tracing, dashboards, alerts, and other useful operational signals.</li> <li value="3"><strong><strong class="textBold">Strengthen</strong></strong> rollout safety, capacity awareness, failure handling, and recovery procedures for production environments.</li> <li value="4"><strong><strong class="textBold">Debug</strong></strong> and resolve complex issues spanning Kubernetes, Linux, networking, storage, workload runtime behaviour, and cloud or datacentre infrastructure dependencies.</li> <li value="5"><strong><strong class="textBold">Enhance</strong></strong> operational playbooks, runbooks, and engineering practices to reduce toil and increase service resilience.</li> </ul> <h2>Team Technical Contribution</h2> <ul> <li value="1"><strong><strong class="textBold">Contribute</strong></strong> to design discussions, code reviews, and operational standards within the platform engineering team.</li> <li value="2"><strong><strong class="textBold">Collaborate</strong></strong> with software engineering, infrastructure, and SRE teams to deliver platform capabilities that are practical, supportable, and aligned to operational needs.</li> <li value="3"><strong><strong class="textBold">Define</strong></strong> sensible defaults, paved roads, and supportable patterns for service deployment and runtime operations.</li> <li value="4"><strong><strong class="textBold">Mentor</strong></strong> less experienced engineers in platform engineering fundamentals, operational judgement, and good automation practices.</li> </ul> <h2>KPIs</h2> <ul> <li value="1"><strong><strong class="textBold">Platform reliability and service resilience</strong></strong></li> <li value="2"><strong><strong class="textBold">Reduction in manual operational toil</strong></strong></li> <li value="3"><strong><strong class="textBold">Incident detection, response, and recovery effectiveness</strong></strong></li> <li value="4"><strong><strong class="textBold">Observability and operational readiness of platform services</strong></strong></li> </ul> <h2>About You</h2> <ul> <li value="1"><strong><strong class="textBold">Strong hands-on experience</strong></strong> operating and improving Kubernetes-based platforms in production.</li> <li value="2"><strong><strong class="textBold">Solid experience</strong></strong> with infrastructure automation, CI/CD, configuration management, or GitOps-style workflows.</li> <li value="3"><strong><strong class