Staff Site Reliability Engineer - Monitoring and Anomaly Detection (Monetization)

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role The Observability, Monitoring, and Integrations team manages observability, monitoring, and detection for systems that support customer purchasing and use of GitLab. As a Staff Backend Engineer on the Fulfillment Workflow Monitoring (Catch All) team, you'll set the technical direction for the telemetry, detection, and reconciliation tooling that identifies billing, data, and event anomalies across CustomersDot, Salesforce, and Zuora before they can affect revenue or the customer experience. This is a greenfield team. You'll help build it from the ground up, shaping its operating rhythm, incident response model, and quality bar. You'll use telemetry and machine learning to identify issues early and help resolve them. Because Monetization changes can directly affect revenue and often involve confidential or financial information, you'll use strong judgment, careful rollout practices, and a high bar for reliability. This role is opening at the Staff Backend Engineer level (grade 8). What you’ll do Design, build, and operate observability across the Monetization stack, including metrics, logs, and traces, using tools such as Prometheus and Grafana. Implement automated detection for billing, data, and event anomalies, and route alerts to the responsible feature teams. Develop reconciliation and data integrity checks across usage and billing pipelines. Define and track service level objectives and service level indicators, write runbooks, and take part in incident response to measure and improve Monetization system reliability. Explore artificial intelligence and machine learning techniques to predict system anomalies and accelerate resolution. Review and offer feedback on merge requests from other Monetization engineers. Collaborate with Product, Finance, Support, and other partners to turn operational needs into reliable tooling. What you’ll bring Professional experience with Ruby on Rails, including building and operating applications such as CustomersDot. Experience in site reliability or observability engineering, including monitoring, alerting, service level objectives and indicators, runbooks, and incident response. Experience setting technical direction for observability, reliability, or detection work and bringing other engineers along. Experience building anomaly detection, monitoring, or risk management tooling. Familiarity with observability tools such as Prometheus, Grafana, and OpenTelemetry. Exposure to analytical data stores such as ClickHouse and the change data capture and event-streaming pipelines that feed them, including Siphon and NATS JetStream. Experience owning projects from concept through production, communicating clearly about complex technical and organizational problems, and proposing iterative solutions. Working knowledge of Python for anomaly detection and data work, or experience with billing, financial, or other business-critical systems, including Zuora or Salesforce, is a plus.