Senior Staff Software Engineer – SRE, Release & Test Platforms

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people.

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: 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.

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. 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