Senior Staff Software Engineer, ServiceNow

• 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
• 12+ years of experience in software, systems, platform, or reliability engineering with a Bachelor's degree; or 8 years and a Master's degree; or a PhD with 5 years experience; or equivalent experience
• Deep Kubernetes expertise across architecture, operations, networking, storage, security, autoscaling, and multi-cluster environments
• Experience building and operating large-scale Kubernetes platforms for cloud-native, mission-critical services
• Experience integrating Kubernetes with CI/CD, GitOps, automated testing, and deployment validation
• Experience designing cloud-native platforms for ephemeral environments, release qualifications, and automated validation
• Proven ability to lead engineering excellence across developer productivity, platform engineering, release confidence, and modernization
• Experience with progressive delivery, including canary releases, feature flags, automated rollback, and deployment verification
• Experience with chaos engineering, resilience validation, disaster recovery, and reliability assessments
• Expertise designing, authoring, testing, and debugging code in a team setting using languages such as Python, Go, Java, or Ruby
• Experience using AI-assisted engineering for intelligent testing, release risk analysis, incident diagnostics, and operational automation
• Strong coding, observability, SLO, and cross-team collaboration skills to improve reliability, performance, and engineering standards

Desirable

• 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
• Build and operate cloud-native engineering platforms for software validation, release qualification, and operational readiness
• Design production-like release and test environments that improve release confidence and deployment readiness
• Develop automated quality gates to assess release health, operational risk, and production readiness
• Integrate automated testing, observability, reliability signals, and deployment intelligence into CI/CD pipelines
• Build reusable test frameworks, self-service environments, test data, mock services, and developer productivity tooling
• Advance shift-left engineering through automated validation, continuous verification, and quality gates
• Automate failure detection, policy validation, deployment verification, security checks, and reliability assessments
• Lead Kubernetes-based platform evolution for scalable test infrastructure, release automation, and developer self-service
• Resolve recurring infrastructure issues through sustainable software, systems, and networking solutions
• Partner with engineering teams on design reviews, architecture standards, and automation-first reliability practices