What you'll be doing

• 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 to 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 to 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 platform, infrastructure, and networking challenges using 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 implement 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

Requirements

• Experience leveraging or critically thinking about AI integration in work processes, decision-making, or problem-solving
• 8+ years of experience in SRE, DevOps, Platform Engineering, Software Engineering, or Infrastructure Engineering with a Bachelor's degree; or equivalent experience with advanced degrees
• Hands-on experience with Kubernetes 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 for developer productivity, release quality, and operational efficiency
• Experience with progressive delivery practices such as 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 experience in Python, Go, Java, or Ruby
• Strong understanding of observability, monitoring, SLI/SLOs, incident management, and production operations for distributed systems
• Ability to solve complex technical problems, drive projects independently, and collaborate effectively across teams
• Thrives in fast-paced, ambiguous environments with a strong ownership mindset, bias for action, and passion for continuous learning and automation
• Low ego, intellectually curious, effective collaborator with experience working in globally distributed teams

Nice to haves

• Experience with observability and monitoring platforms for applications and distributed systems at scale
• Experience with DevOps automation, CI/CD pipelines, GitOps, and Agile development tools such as GitLab CI/CD, Argo CD, or Flux
• Experience building and maintaining enterprise-scale test automation frameworks like Playwright, Selenium, Cypress, REST Assured, PyTest, or JUnit/TestNG
• Experience with test orchestration, intelligent regression testing, test impact analysis, flaky test detection, parallel execution, and test data management
• Experience with service virtualization, contract testing, synthetic testing, and building developer self-service engineering platforms
• Experience with Infrastructure as Code and configuration management tools such as Ansible or Terraform
• Experience with Kubernetes ecosystem tools including Helm, Argo Workflows, Kustomize, Istio/Linkerd, Gateway API/Ingress, Prometheus, OpenTelemetry, and container runtimes
• Experience operating Kubernetes platforms on public clouds like AWS (EKS), Azure (AKS), and Google Cloud (GKE)
• Familiarity with AI-assisted engineering, intelligent testing, operational automation, or cloud-native engineering platforms
• Experience leveraging AI-assisted engineering for intelligent testing, release risk analysis, incident diagnostics, or operational automation