AI Operations Engineer

The AI Operations Engineer helps operate and improve SolarWinds' approved AI platforms, connectors, automations, and supporting controls. The role works across platform administration, identity and access, integrations, usage and spend reporting, policy enforcement, and enablement so employees can adopt AI tools effectively, securely, and with minimal friction.

Because AI tools at SolarWinds draw on data from the wider application estate, the engineer is expected to be a capable general systems engineer first. They need to work comfortably in Microsoft 365, Google Workspace, and the identity layer behind them, and to understand how connected business applications feed and are governed by the AI platforms.

This engineer owns small-to-medium operational tasks and workflows end to end, brings larger design or risk decisions to IT leadership for alignment, and increasingly identifies improvements without being asked.

Core Responsibilities:

• Administer and monitor the approved AI tool stack, including user and group provisioning, licensing, configuration, connectors, audit logs, and DLP settings.
• Operate and troubleshoot connectors and integrations that bring enterprise data into AI platforms (for example Microsoft 365 / SharePoint / OneDrive / Teams, Google Workspace, Slack, Atlassian, Salesforce, GitHub, Zoom, and similar), including permission mirroring, sync failures, and data-source hygiene.
• Support identity and access for AI platforms: SSO and SCIM configuration, group-based access, service accounts, API tokens, and OAuth/MCP client registrations, following established standards.
• Resolve operational issues and user-reported problems, identify root causes, and apply durable fixes where scope allows; for complex or cross-system issues, document findings and a recommended path forward.
• Build and maintain scripts, automations, and workflows using APIs, platform-native tooling, and service accounts to reduce manual effort (for example provisioning, reporting, license reclamation, and audit exports).
• Own usage metering, spend tagging, license hygiene, and vendor-reporting processes; produce regular adoption and consumption reporting for IT leadership.
• Support guardrail enforcement and policy compliance monitoring, including allowlists, access reviews, usage limits, logging, and evidence collection for Security, GRC, and Legal.
• Triage and process intake requests for new AI integrations, connectors, and tools, and prepare clear technical assessments for review.
• Create and maintain documentation, runbooks, and knowledge articles so repeated work is consistent and transferable.
• Contribute to training content, office hours, and adoption reporting to help teams use approved AI tools well.
• Follow change control and service management practices, and keep platform configuration, tickets, and documentation current and auditable.
• Partner with IT, Security, Business Applications, Procurement, and Engineering to move work forward.

Qualifications

Required:

• 2–4 years of relevant experience in IT operations, systems engineering, cloud administration, or AI/SaaS platform management.
• Hands-on administration experience with Microsoft 365 (Entra ID, Exchange Online, SharePoint/OneDrive, Teams, Intune or equivalent) and Google Workspace (Admin console, Drive sharing and permissions, Google Groups, Gmail), in an enterprise or similarly sized environment.
• Working knowledge of identity and access management: SSO (SAML/OIDC), SCIM provisioning, MFA and Conditional Access, group-based access models, service accounts, and API tokens or OAuth scopes.
• Experience administering SaaS platforms and integrating them with other systems, such as Slack, Atlassian (Jira/Confluence), Salesforce, GitHub, Zoom, or similar collaboration and business applications.
• Experience with scripting or automation (for example PowerShell, Python, or Bash) and with consuming REST APIs.
• Ability to troubleshoot operational issues methodically and document root cause and resolution.
• Working knowledge of audit logging, observability or monitoring tools, and basic compliance evidence practices.
• Ability to write clear technical documentation and runbooks.
• Good communication skills with technical and non-technical stakeholders.
• Bachelor's degree in a related field or equivalent experience.

Preferred:

• Exposure to enterprise AI platforms and tools such as Glean, Claude, Microsoft Copilot, ChatGPT Enterprise, or workflow/agent platforms, in an administration, enablement, or governance capacity.
• Familiarity with how AI connectors, permission-aware search, and Model Context Protocol (MCP) integrations work.
• Experience with cloud platforms and AI services (GCP/Vertex AI, AWS/Bedrock, or Azure).
• Basic understanding of FinOps practices such as usage metering, cost tagging, and license optimization.
• Familiarity with data governance concepts, DLP, and data classification.
• Experience with ITSM and change management tooling.
• Nice to have (development background):
• Experience writing and maintaining code in Python, JavaScript/TypeScript, or similar, including use of Git, code review, and basic CI/CD.
• Experience building small integrations, API clients, webhooks, or serverless functions.
• Experience with low-code or workflow automation platforms.
• Exposure to SQL and data tooling such as BigQuery for usage and cost reporting.
• Interest in or experience with building simple AI agents or prompt-based workflows.