> Markdown version of [/jobs/ext/1732987-senior-site-reliability-engineer-aiops](https://www.wearedevelopers.com/jobs/ext/1732987-senior-site-reliability-engineer-aiops). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Site Reliability Engineer, AIOPs - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $148,000.0 - $235,750.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Systems Engineering, Bash Shell, Computer Programming, Computer Graphics, Continuous Integration, Data Centers, Data Integrity, Software Debugging, Linux, DevOps, Distributed Systems, Python (Programming Language), Reliability Engineering, Prometheus, Software Deployment, Software Engineering, Scripting, Grafana, Apache Spark, Kubernetes, Apache Flink, Apache Kafka, Vertica, Terraform, Stream Processing, Microservices - **Published:** July 28, 2026 - **Apply:** https://www.juju.com/job/00000000gk2swv ## About the Role + BS/MS in CS/CE (or equivalent experience) and 5+ years operating production distributed systems as SRE/DevOps/Platform Ops. + Proven ownership of reliability for an observability/AIOps platform: SLOs/SLIs, on-call, addressing incidents, and follow-up evaluations that drive measurable improvements. + Deep Kubernetes + containers experience (deploying, debugging, scaling) for telemetry-heavy microservices-ingestion, processing, storage, APIs, and UI. + Automation-first approach: solid scripting (Python/Bash), CI/CD, and infrastructure-as-code (Terraform + Helm) to deliver safe rollouts (canaries/rollbacks), reproducible environments, and minimal toil. + Clear communicator who writes excellent runbooks/docs and can translate ambiguous requirements into concrete operational practices and dependable customer-facing reliability. Ways to stand out from the crowd: + Strong Linux + networking fundamentals, distributed systems instincts, and hands-on ops for Kubernetes/services/streaming stacks are ideal; bonus for experience with observability platforms at scale. + Experience building safe automation that operators trust: canary releases, automated rollback criteria, "monitoring for the monitoring" (lag/drop/error budgets), and replay/backfill pipelines with correctness checks. + Strong in distributed/streaming systems operations (Kafka/Pulsar, Flink/Spark, ClickHouse/Elastic/TSDBs, object storage)-and can reason about backpressure, hotspots, and failure domains end-to-end. + Proven programming experience building automation tools or services - ideally in Python, or similar languages - to simplify operations and scale recurring processes. + Proven experience running large-scale production deployments and multiple Kubernetes environments or clusters across teams or customers, coordinating changes and rollouts with minimal disruption with hands-on experience with observability tools - you know your way around dashboards, metrics, logs, and traces using platforms like Prometheus, Grafana, or similar. ## Description 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. Join our team of innovative engineers who are building an AI Data Center AIOps platform that turns raw, high-volume telemetry into reliable, job-centric insights and automation for GPU fleets. We're hiring a DevOps Engineer to operate the platform itself (not the compute cluster): uptime, performance, data integrity, and safe change management. You'll own SLOs/SLIs, incident response, and postmortems for the telemetry ingestion, processing, storage, and APIs/dashboards that operators depend on. You'll partner Software Engineering and Systems Engineering team to translate platform signals into actionable, trustworthy alerts and automation. What you'll be doing: + Continuously monitor platform health via dashboards/logs/metrics, automate recurring checks, and keep reliability + resource efficiency on track. + Own Kubernetes deployments end-to-end (runbooks, canary checks, post-deploy validation), and lead rollbacks/remediations when needed. + Lead first-level incident triage: collect diagnostics, identify likely root causes, and hand off clear, actionable findings to engineering. + Build and maintain runbooks/SOPs/checklists, pushing continuous improvement through automation. + Manage deployment infrastructure and packaging (Helm + Terraform/IaC) to keep environments scalable, consistent, and reproducible. + Contribute in adjacent functional areas to grow and help your team members! ## Related Videos - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [#90DaysOfDevOps - The DevOps Learning Journey](https://www.wearedevelopers.com/videos/548-90daysofdevops-the-devops-learning-journey) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) ## Related Articles - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)