Staff Reliability Engineer

Join us to build the next generation of cloud-native reliability, release, and test platforms that enable engineering excellence, developer productivity, and high-confidence ServiceNow releases through automation, observability, and AI-driven operations. What you get to do in this role: Design, build, and operate cloud-native engineering platforms for software validation, release validation, and production readiness Design and maintain production-like release and test ServiceNow environments that improve release confidence and deployment readiness. Build and integrate automated test pipelines, observability, reliability signals, deployment intelligence, and quality gates into CI/CD workflows. Develop automation solutions that improve engineering productivity, streamline operations, and reduce manual toil through shift-left engineering practices. Build reusable frameworks, self-service engineering environments, test data management, mock services, and developer productivity tooling. Design and enhance Kubernetes-based platforms supporting scalable test infrastructure, release automation, cloud-native workloads, and developer self-service. Implement automated validation for failure detection, deployment verification, policy enforcement, security checks, resilience testing, and operational health assessments. Resolve complex platforms, infrastructure, and networking challenges through software engineering, systems design, and automation. Partner closely with engineering teams to improve platform reliability, release quality, cloud-native adoption, and engineering best practices. Participate in architecture reviews, technical design discussions, and implementation of scalable, automation-first engineering solutions. Influence technical decisions through strong engineering execution, collaboration, and delivery of high-quality platform capabilities. Mentor engineers through technical guidance, code reviews, knowledge sharing, and engineering best practices. Foster a culture of reliability, automation, operational excellence, continuous improvement, and customer-focused engineering.

To be successful in this role you have: Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry. 8+ years of experience in Site Reliability Engineering (SRE), DevOps, Platform Engineering, Software Engineering, or Infrastructure Engineering with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience. Hands-on experience with Kubernetes across cluster operations, networking, storage, security, autoscaling, and multi-cluster environments. Experience building and operating cloud-native platforms supporting scalable, highly available services. Experience integrating Kubernetes with CI/CD, GitOps, automated test pipelines, deployment validation, and cloud-native deployment workflows. Experience designing and implementing automation to improve developer productivity, release quality, and operational efficiency. Experience with progressive delivery practices, including canary deployments, feature flags, automated rollback, and deployment verification. Experience with chaos engineering, resilience testing, disaster recovery, and reliability validation. Strong software engineering skills with hands-on experience designing, developing, testing, and debugging applications using Python, Go, Java, or Ruby. Experience leveraging AI-assisted engineering for intelligent testing, release risk analysis, incident diagnostics, or operational automation is a plus. Strong understanding of observability, monitoring, SLI/SLOs, incident management, and production operations for distributed systems. Demonstrated ability to solve complex technical problems, drive projects independently, and col