Staff Systems Engineer, IT

An Overview of This Role Staff Systems Engineer, IT is a senior, hands-on engineering role for a generalist who is comfortable owning a broad set of platforms. You'll own the systems and integrations behind the employee lifecycle, onboarding, role changes, and offboarding, and you'll build them the way we build software: as infrastructure-as-code, with SRE practices behind them so they are versioned, observable, and reliable. You'll be the technical owner of GitLab's ITSM platform and the AI capabilities layered on top of it, designing virtual agents, agentic workflows, and knowledge experiences that resolve requests before they ever become tickets. You'll also own IT infrastructure across our cloud footprint. Working with our AI-enabled ITSM, you'll replace repetitive manual work with durable automation, and you'll partner with End User Services, Security, People, and Finance to scale those solutions company-wide. You'll be measured on automation coverage of lifecycle processes, AI deflection rates, and the reliability of the systems you build. - The GitLab Team Member Handbook What You'll Do - Design, build, and own end-to-end automation for the employee lifecycle - onboarding, transfers, role changes, and offboarding - so provisioning and deprovisioning happen accurately and with minimal human touch. - Serve as the technical owner of GitLab's ITSM platform, including service catalog design, workflow, request/incident/change processes, integrations, and platform upgrades. - Increase AI deflection rates for all stakeholders of the ITSM system by deploying and tuning virtual agents, AI search, and agentic resolution, and by measuring what actually resolves requests without human intervention. - Identify repetitive, manual workflows across IT and its partner teams and replace them with automation built in our ITSM and Serval. - Build and maintain integrations between the ITSM platform and GitLab's core systems, including Okta, Google Workspace, Slack, Zoom, JAMF, Fleet, Workday, and GitLab itself. - Manage IT-owned infrastructure as code across our cloud environments, so every change ships through version control, code review, and an automated, auditable path to production. - Apply SRE principles to the services IT owns: meaningful monitoring and alerting, clear reliability targets, capacity and cost awareness, and blameless post-incident review. - Develop the knowledge management and self-service experiences that feed AI deflection: well-structured articles, catalog items, and conversational flows that stay accurate as systems change. - Instrument automation and AI performance with clear metrics and dashboards, deflection rate, time to resolution, automation coverage, and failure rates, and iterate publicly on the results. - Set engineering standards for the IT automation stack, including version control, testing, code review, environment management, and change control, and mentor support engineers across the IT organization. - Partner with Security and Compliance to ensure lifecycle automation and AI workflows meet access, audit, and control requirements, including SOX and SOC 2. - Document architecture, runbooks, and design decisions in the handbook so the systems you build are transparent, maintainable, and operable by the whole team. What You'll Bring - Breadth as a generalist systems engineer. You have owned a wide range of platforms end to end, and you pick up unfamiliar ones fast enough to own them outright. - Solid infrastructure-as-code experience (Terraform or similar), with change managed through version control, code review, and automated deployment rather than manual, one-off work. - A working command of SRE principles, including observability, monitoring and alerting, reliability targets, and blameless post-incident review, applied to the services you own. - Experience running workloads in a major public cloud; working knowledge across all three (AWS, GCP, and Azure) is a plus. - Experience designing or