Senior Site Reliability Engineer, Wikimedia Enterprise

The Wikimedia Foundation is looking for a Senior Site Reliability Engineer to join our team, reporting to the Sr. Engineering Manager. In this role, you will design, develop, and maintain reliable infrastructure for our API services while collaborating across departments to enhance system reliability and performance.

Responsibilities:

• Define, track, and improve Service Level Objectives (SLOs), SLIs, and error budgets to ensure reliability targets are met
• Build and enhance observability systems (metrics, logs, and distributed tracing) to enable proactive detection and faster troubleshooting
• Drive reliability engineering practices, including capacity planning, load testing, and resilience validation (e.g., chaos testing)
• Improve developer experience (DevEx) by enabling self-service infrastructure and streamlining deployment workflows
• Partner with engineering team members to embed reliability best practices early in the development lifecycle
• Design, implement, and optimize CI/CD and GitOps workflows using tools such as GitLab (or similar) and ArgoCD(or similar), enabling automated, reliable deployments with support for progressive delivery strategies like canary and blue-green releases
• Implement secure-by-default infrastructure and enforce best practices (e.g., IAM, secrets management, encryption)
• Continuously optimize infrastructure cost and efficiency using FinOps principles while maintaining performance and availability
• Establish and track operational metrics such as MTTR, MTTD, and incident frequency to drive continuous improvement
• Reduce operational toil by identifying repetitive work and implementing automation-first solutions
• Contribute to and evolve internal platform capabilities that standardize infrastructure and improve scalability across teams
• Collaborating with a global and asynchronously communicating team (don’t worry if you have never worked remotely, we’ll help you get used to it)
• Mentoring peers in your areas of technical and operational strength

Requirements:

• Define, track, and improve Service Level Objectives (SLOs), SLIs, and error budgets to ensure reliability targets are met
• Build and enhance observability systems (metrics, logs, and distributed tracing) to enable proactive detection and faster troubleshooting
• Drive reliability engineering practices, including capacity planning, load testing, and resilience validation (e.g., chaos testing)
• Improve developer experience (DevEx) by enabling self-service infrastructure and streamlining deployment workflows
• Partner with engineering team members to embed reliability best practices early in the development lifecycle
• Design, implement, and optimize CI/CD and GitOps workflows using tools such as GitLab (or similar) and ArgoCD(or similar), enabling automated, reliable deployments with support for progressive delivery strategies like canary and blue-green releases
• Implement secure-by-default infrastructure and enforce best practices (e.g., IAM, secrets management, encryption)
• Continuously optimize infrastructure cost and efficiency using FinOps principles while maintaining performance and availability
• Establish and track operational metrics such as MTTR, MTTD, and incident frequency to drive continuous improvement
• Reduce operational toil by identifying repetitive work and implementing automation-first solutions
• Contribute to and evolve internal platform capabilities that standardize infrastructure and improve scalability across teams
• Collaborating with a global and asynchronously communicating team (don't worry if you have never worked remotely, we'll help you get used to it)
• Mentoring peers in your areas of technical and operational strength
• Automation & Configuration Management: Experience with Infrastructure as Code and automation tools (e.g., Terraform, Ansible) and proficiency in at least one programming language (e.g., Python, Go, or similar)
• Cloud Infrastructure: Experience designing, operating, and optimizing cloud-based systems across platforms such as AWS, Azure, or GCP, including scalability, reliability, and cost efficiency
• CI/CD & Deployment Practices: Experience building and maintaining CI/CD pipelines and GitOps workflows (e.g., GitLab or similar, ArgoCD), with familiarity in progressive delivery approaches such as canary and blue-green deployments
• Incident Management & Reliability Operations: Experience with incident response, on-call practices, and leading postmortems, with a focus on continuous improvement and operational excellence
• SRE Principles & Observability: Strong understanding of SRE best practices, including SLOs, SLIs, and error budgets, along with experience in observability (metrics, logging, and distributed tracing e.g., Prometheus, OpenTelemetry)
• Collaboration & Communication: Ability to work effectively in a distributed, cross-functional environment, with strong documentation and communication skills
• Proven experience operating highly available, large-scale distributed systems, with a deep understanding of reliability, scalability, and failure modes
• Ownership mindset: Takes end-to-end responsibility for system reliability, proactively identifying and addressing risks before they impact users
• Bias for automation: Continuously seeks to reduce operational toil through automation and scalable solutions
• Continuous improvement mindset: Actively learns from incidents and drives improvements through blameless postmortems and iterative enhancements
• Customer and reliability focus: Prioritizes user experience by balancing availability, performance, and cost
• Adaptability and learning: Comfortable working in a fast-evolving environment and learning new tools and technologies as needed
• Experience managing and troubleshooting event streaming platforms at scale (e.g., Kafka, Kinesis, or similar)
• Hands-on experience with cloud platforms such as AWS and/or GCP, including designing and operating production systems
• Familiarity with data lake architectures and large-scale data processing frameworks (e.g., Iceberg, Flink, Spark)
• Experience with continuous profiling and performance optimization tools to identify bottlenecks and improve system efficiency
• Experience working with or contributing to open source projects, particularly in infrastructure or data ecosystems
• Prior participation in the Wikimedia movement