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ServiceNow is seeking a Staff Site Reliability Engineer to design, build, and operate cloud-native engineering platforms that support software validation, release validation, and production readiness. This is a high-impact technical role where you'll architect and maintain production-like environments, build automated test pipelines with observability and quality gates, and develop automation solutions that reduce manual toil through shift-left engineering practices.
Key responsibilities include:
- Design and build Kubernetes-based platforms supporting scalable test infrastructure, release automation, and developer self-service
- Integrate automated test pipelines, observability, reliability signals, and deployment intelligence into CI/CD workflows
- Develop reusable frameworks, self-service engineering environments, and developer productivity tooling
- Implement automated validation for failure detection, deployment verification, policy enforcement, security checks, and resilience testing
- Resolve complex platform, infrastructure, and networking challenges through software engineering and systems design
- Partner with engineering teams to improve platform reliability, release quality, and cloud-native adoption
- Participate in architecture reviews and technical design discussions
- Mentor engineers through technical guidance, code reviews, and knowledge sharing
- Foster a culture of reliability, automation, and continuous improvement
This role emphasizes technical leadership and influence through strong engineering execution, collaboration, and delivery of high-quality platform capabilities. You'll work on mission-critical infrastructure that impacts the entire engineering organization.
Requirements:
- 8+ years of experience in Site Reliability Engineering, DevOps, Platform Engineering, Software Engineering, or Infrastructure Engineering (with Bachelor's degree); or 6 years with Master's degree; or PhD with 3+ years experience; or equivalent
- 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, and cloud-native deployment workflows
- Experience designing and implementing automation to improve developer productivity, release quality, and operational efficiency
- Experience with progressive delivery practices (canary deployments, feature flags, automated rollback, deployment verification)
- Experience with chaos engineering, resilience testing, disaster recovery, and reliability validation
- Strong software engineering skills with hands-on experience in Python, Go, Java, or Ruby
- 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 collaborate effectively
- Ownership mindset, bias for action, passion for continuous learning and automation
- Experience leveraging or critically thinking about how to integrate AI into work processes and problem-solving
Preferred qualifications:
- Experience with observability and monitoring platforms at scale
- DevOps automation, CI/CD pipelines, GitOps using GitLab CI/CD, Argo CD, or Flux
- Enterprise-scale test automation frameworks (Playwright, Selenium, Cypress, REST Assured, PyTest, JUnit/TestNG)
- Test orchestration, intelligent regression testing, test impact analysis, flaky test detection
- Service virtualization, contract testing, synthetic testing
- Infrastructure as Code tools (Ansible, Terraform)
- Kubernetes ecosystem tools (Helm, Argo Workflows, Kustomize, Istio/Linkerd, Prometheus, OpenTelemetry)
- Operating Kubernetes on AWS (EKS), Azure (AKS), Google Cloud (GKE)
- AI-assisted engineering and intelligent testing
