Generative AI Solutions Engineer

The Generative AI Solutions Engineer develops and supports data integrations, reporting, automation, and AI-enabled solutions with an emphasis on enterprise data and analytics. The position is responsible for supporting the initial design, development and operationalization of enterprise AI agents that serve student success needs. Working across the organization, the Generative AI Solutions Engineer supports data governance, quality monitoring, metadata, lineage, tagging, and traceability to trusted sources.

• Develop, configure, test, and maintain student, advisor, and staff-facing AI agents using Microsoft Copilot Studio, Azure AI, Microsoft Fabric, and related technologies.
• Translate business use cases into technical requirements, solution designs, data requirements, prototypes, and testing plans.
• Build prompts, workflows, connectors, knowledge sources, integrations, and retrieval-augmented generation solutions using approved institutional data and documents.
• Monitor and troubleshoot enterprise solutions.
• Document AI architecture, data sources, testing results, safeguards, limitations, and responsible AI practices.

• Develop and maintain data quality rules, validation processes, monitoring, and certification of trusted data assets and reports.
• Profile data and investigate errors; coordinate root-cause analysis and remediation.
• Apply and maintain data tags and approved definitions across enterprise platforms.
• Maintain metadata, automated harvesting, synchronization, and end-to-end lineage across systems.

• Develop, test, monitor, and maintain data integration pipelines, Fabric assets, APIs, and related platform components using approved source-control, testing, deployment, security, and change-management practices.
• Onboard and integrate enterprise data sources, applications, files, APIs, and external services; build and validate extraction, transformation, reconciliation, loading, and automation processes.
• Document mappings, data flows, and operating procedures; troubleshoot pipeline failures, and performance issues.

• Develop and maintain Power BI dashboards, semantic models, analytical reports.
• Create dashboards that monitor AI performance, adoption, data quality, lineage, metadata, and pipeline reliability

• Bachelor’s degree in computer science, information systems, data analytics, or a related field, or an equivalent combination of education and experience.
• At least 3-5 years of related experience in data integration, software development, analytics, automation, or reporting, and 2 years of experience with AI-enabled solutions.
• Working knowledge of SQL and experience with Python or another relevant programming or scripting language.
• Experience with one or more cloud data, integration, reporting, or automation platforms.
• Experience working with APIs, structured data, data validation, and technical troubleshooting.
• Strong problem-solving, documentation, communication, and collaboration skills, including the ability to translate defined business needs into practical solutions.

• Experience with Microsoft Fabric, Azure, Power BI, Copilot Studio, or related Microsoft technologies.
• Experience developing or supporting AI agents, copilots, chatbots, workflow automation, or analytical solutions.
• Familiarity with source control, testing, deployment, data quality, privacy, security, or responsible AI practices.
• Experience working in higher education or with administrative systems such as student, ERP, CRM, or learning management platforms.

• Typical office setting…