Job Description
Please Note:
Due to Government of Canada regulatory requirements, this position requires the successful completion of a Government of Canada Reliability Status screening as a condition of employment. The screening process requires 5 years of verifiable background history. This includes identity verification, education verification, a criminal record check, and a credit check. Candidates must be eligible to obtain and maintain Reliability Status, which generally requires Canadian citizenship or Canadian permanent resident status.
Employment is contingent upon successful completion and maintenance of the required screening.
About the Team
The Service Now SRE team is a group of highly technical engineers responsible for maintaining and improving the reliability, scalability, and performance of Service Now's cloud infrastructure. You'll design and operate cloud-native platforms for software validation, release validation, and production readiness, and partner with globally distributed engineering teams.
The Role
As a Staff SRE, you'll set the technical direction for reliability and release quality across multiple teams. You'll build the platforms and automation that let engineers ship safely at scale, shape architecture decisions, and raise the bar for operational excellence through hands-on work and mentorship.
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 environments.
- Build automated test pipelines, observability, and quality gates into CI/CD workflows.
- Reduce manual toil through automation and shift-left practices.
- Build reusable frameworks, self-service environments, test data management, and mock services.
- Design and enhance Kubernetes-based platforms for test infrastructure, release automation, and developer self-service.
- Implement automated checks for failure detection, deployment verification, policy enforcement, security, and resilience.
- Resolve complex platform, infrastructure, and networking challenges.
- Lead architecture reviews and design discussions, and drive projects independently across teams.
- Mentor engineers through code reviews, guidance, and knowledge sharing.
- Promote a culture of reliability, automation, and operational excellence.
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 SRE, Dev Ops, platform, software, 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 Kubernetes experience across cluster operations, networking, storage, security, autoscaling, and multi-cluster environments.
- Experience building and operating highly available cloud-native platforms.
- Experience integrating Kubernetes with CI/CD, Git Ops, automated test pipelines, and deployment validation.
- Experience with progressive delivery, including canary deployments, feature flags, and automated rollback.
- Experience with chaos engineering, resilience testing, and disaster recovery.
- Strong software engineering skills in Python, Go, Java, or Ruby.
- Solid understanding of observability, SLIs/SLOs, incident management, and distributed systems operations.
- Ability to drive projects independently and thrive in fast-paced, ambiguous environments, with a strong ownership mindset.
- Experience integrating AI into work processes, decision-making, or problem-solving.
Preferred Qualifications
- Observability and monitoring platforms at scale, including Grafana and Victoria Metrics.
- Dev Ops and Git Ops tools such as Git Lab CI/CD, Argo CD, or Flux.
- Test automation frameworks such as Playwright, Selenium, Cypress, REST Assured, PyTest, or JUnit/TestNG.
- Test orchestration, flaky test detection, and test data management.
- Service virtualization, contract testing, and synthetic testing.
- Infrastructure as Code with Terraform or Ansible.
- Kubernetes ecosystem tools such as Helm, Istio/Linkerd, Prometheus, and Open Telemetry.
- Managed Kubernetes on AWS (EKS), Azure (AKS), or Google Cloud (GKE).
- AI-assisted engineering, intelligent testing, or operational automation.
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