Senior Site Reliability Engineer, Wikimedia Enterprise

Accountabilities

In this role, you will be responsible for ensuring the reliability, scalability, and performance of large-scale distributed systems that power data and API services. You will:

• Define, track, and continuously improve SLOs, SLIs, and error budgets for critical services


• Design and enhance observability systems including metrics, logging, and distributed tracing


• Participate in incident response, on-call rotations, and post-incident reviews to drive continuous improvement


• Build and maintain CI/CD and GitOps pipelines enabling secure, automated, and reliable deployments


• Implement infrastructure-as-code and automation-first practices to reduce operational toil


• Design and operate scalable cloud infrastructure across production environments


• Drive capacity planning, performance optimization, and resilience testing (including chaos engineering practices)


• Improve developer experience by enabling self-service infrastructure and streamlined workflows


• Collaborate with security, software, and release engineering teams to embed reliability and security best practices


• Optimize infrastructure cost and efficiency using FinOps principles without compromising availability


• Develop and maintain operational metrics such as MTTR, MTTD, and incident frequency


• Contribute to platform engineering initiatives that standardize infrastructure across teams


• Mentor peers and promote best practices in SRE, automation, and systems reliability

Requirements
This position requires strong expertise in site reliability engineering, distributed systems, and cloud infrastructure, along with a proactive and collaborative mindset. You should have

• 5+ years of experience in SRE, DevOps, or infrastructure engineering roles


• Strong experience with infrastructure-as-code tools such as Terraform and/or Ansible


• Proficiency in at least one programming language (Python, Go, or similar)


• Hands-on experience with cloud platforms such as AWS, GCP, or Azure


• Experience building and maintaining CI/CD pipelines and GitOps workflows (e.g., GitLab, ArgoCD or similar tools)


• Strong understanding of SRE principles including SLOs, SLIs, and error budgets


• Experience with observability tooling such as Prometheus, OpenTelemetry, or equivalent


• Proven experience in incident response, on-call operations, and postmortem analysis


• Ability to operate and optimize large-scale distributed systems with high availability requirements


• Strong communication and collaboration skills in distributed, remote-first environments


• Ability to document systems clearly and contribute to shared engineering knowledge


• Strong ownership mindset, with a focus on automation, reliability, and continuous improvement


• Adaptability to fast-evolving, technology-driven environments

• Remote-first work model with global collaboration


• Opportunity to work on high-impact systems supporting global knowledge platforms


• Exposure to large-scale distributed systems and modern cloud-native architectures


• Culture of engineering excellence, automation, and continuous improvement


• Strong emphasis on learning, experimentation, and open collaboration


• Competitive compensation adjusted to location and experience


• Inclusive and diverse work environment with global team exposure


• Opportunity to contribute to open knowledge infrastructure used worldwide

This listing is from ats_lever. View original listing ↗