HiredNow AI
Origami Risk LLC

Engineering Systems Engineer - Azure DevOps Administration & Governance

$100,000 to $122,000 a year

  • Remote, US
  • Full time

Found by HiredNow AI on Oct 8, 2024. Subscribers saw it first.

About the role

Overview

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.

Starting base pay for this role is between $100,000 and $122,000. The actual base pay is dependent upon many factors, such as transferable skills, work experience, business needs, training, location, and market demands. The base pay range is subject to change and may be modified in the future. This role will be eligible for a bonus as well as competitive medical, dental, and vision benefits, wellness reimbursement, life insurance, and a 401(k) with company match. We offer vacation and sick leave benefits (under a flexible time off policy in most states).

Responsibilities

Azure DevOps Administration & Governance (45%)• Owns day-to-day administration of Azure DevOps across the Engineering organization — managingorganizations, projects, teams, boards, area paths, iteration cadences, and access controls with theconsistency, precision, and configuration hygiene that a multi-team Engineering organization depends on.Pipeline authoring and CI/CD configuration are owned by the engineering teams themselves, not this role.• Takes command of ADO governance and standardization — establishing and enforcing project structurestandards, naming conventions, board configurations, and workflow approaches that prevent thefragmentation that comes from ad hoc, admin-by-admin configuration choices.• Reviews and manages workflow configuration requests from Engineering teams — diagnosing the actualbusiness problem behind each request, identifying root causes, and proposing better solutions rather thanband-aid fixes like unnecessary fields or workaround processes.• Owns the administrative side of the Azure DevOps ↔ GitHub integration — repository links, GitHubApps/OAuth connections, and work item linking — that connect Azure DevOps Boards to our GitHub-hosted repos, since our source code lives in GitHub rather than Azure Repos. Configuring pipeline-specificservice connections and triggers is owned by the teams that build those pipelines.• Manages Azure DevOps user provisioning, permission models, and access reviews — ensuring access isscoped to least-privilege principles, regularly audited, promptly revoked when no longer needed, anddocumented to support compliance evidence requirements.• Monitors Azure DevOps platform health, usage patterns, adoption metrics, and configuration drift —proactively identifying workflow anomalies, over-provisioned permissions, and opportunities tostandardize before those gaps create friction or risk.• Serves as the primary escalation point for Azure DevOps configuration issues — diagnosing platform-levelincidents, working with Microsoft support when required, and resolving disruptions with the urgency that aplatform used by every engineer in the organization demands.• Leverages AI tools to accelerate platform analysis and administration work — including AI-assistedworkflow and governance configuration audits, AI-generated access audit summaries, and LLM-assistedplatform documentation that keeps governance records current and discoverable.

Automation & Scripting (15%)• Continuously identifies and eliminates manual administration toil across Azure DevOps — buildingPowerShell scripts, REST API automations, and workflow integrations that replace repetitive manual stepswith reliable, auditable automated processes.• Develops and maintains monitoring and alerting for Azure DevOps platform health — including permissionanomalies, configuration drift detection, and provisioning issues — so that platform degradation isdetected and resolved proactively rather than reactively.• Automates access review processes, provisioning workflows, and compliance documentation generation— using scripting and AI tooling to maintain audit-ready governance records without proportional manualoverhead.• Builds automation to enforce ADO standards — naming-convention checkers, board/process-templatevalidation scripts, and configuration-compliance automations that prevent non-standard workflows frombeing deployed without a deliberate override.

Cross-Platform Support — Other Engineering Systems Tooling (15%)• Administers and supports LaunchDarkly, Flyway, and Cursor/AI tooling operations — assisting withprovisioning, access controls, configuration governance, and platform health monitoring alongside theteammate(s) who own each platform.• Maintains unified provisioning standards, least-privilege access principles, and audit-ready access recordsacross Azure DevOps, LaunchDarkly, Flyway, and AI tooling, so governance discipline doesn't stop at theADO boundary.• Monitors integration health across administered systems — SDK evaluation errors, migration failures, andtooling provisioning issues — before they impact Engineering operations.• Builds cross-platform fluency over time, with the expectation of taking on deeper ownership of a secondEngineering Systems platform domain — LaunchDarkly, Flyway, GitHub, or another tool the team adds tothe portfolio — as the role matures. The specific set of “other tools” is not fixed and will shift as the team'sresponsibilities evolve.

Engineering Standards Administration (15%)• Serves as the operational executor of the Engineering standards program — maintaining, publishing,formatting, and distributing standards documentation for coding conventions, branching strategies, pullrequest practices, code review requirements, and tooling usage as directed by the Engineering SystemsManager.• Owns the standards repository — ensuring documentation is accurately organized, consistently formatted,discoverable through the Engineering knowledge base, and immediately updated when standards areratified or revised.• Monitors Engineering standards adherence across teams — identifying non-compliance patterns in codereviews, board and workflow configurations, branch naming, and tooling usage, and bringing specific, data-backed observations to the Engineering Syst

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