The Engineering Systems Engineer, Azure DevOps is the hands-on technical owner of Azure DevOps across the Engineering organization — the project and organization structure, boards, work item process, and access model that every engineer depends on every day, including the integration points that connect Azure DevOps to our GitHub-hosted repos (our source code lives in GitHub, not Azure Repos). Pipeline authoring and CI/CD ownership sit with the engineering teams that build them; this role owns everything else about how Azure DevOps is organized, governed, and accessed. This individual contributor owns Azure DevOps administration, governance, and continuous improvement end-to-end, and is the organization's go-to expert when Azure DevOps issues need to be diagnosed and resolved with authority. This engineer is a proactive platform operator who identifies configuration drift and fragmented workflows before they become embedded patterns, closes governance gaps before they accumulate into technical debt, and automates manual administration work before it creates toil. When a team asks for a workaround, this person diagnoses the actual problem behind the request rather than bolting on a quick fix that adds to the fragmentation. Beyond Azure DevOps, this role also supports the broader Engineering Systems platform portfolio — including LaunchDarkly feature flag operations, Flyway database migration standards, AI-assisted development tools like Cursor and Claude Code, and other tools the team takes on as needed — working alongside teammates who own those platforms and building the working knowledge needed to contribute to cross-platform initiatives. Azure DevOps ownership is the primary responsibility in this role; the rest of the portfolio is secondary and grows with tenure, and the specific list of “other tools” is expected to change over time. This engineer leverages AI throughout their own workflow — using it to accelerate Azure DevOps platform analysis, generate automation scripts, produce enablement documentation, and surface insights from platform data that would take hours to find manually.
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Job Type
Full-time
Career Level
Mid Level