AI Engineer

We are seeking an AI Engineer to bring AI capabilities into our data, reporting, and analytics environment. You will design, build, and deploy AI solutions - LLM-based assistants, autonomous agents, and AI orchestration workflows - that operate on enterprise data and enhance how the organization consumes insights. A flagship example: enriching existing Power

BI reports with AI-generated analysis, narratives, and insights.

The role is approximately 70% AI engineering and 30% Power BI development. You will work closely with the lead of our data warehouse and reporting platform, contributing to the evolution of selected Power BI reports and semantic models while building the AI layer that enhances how users consume insights.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

• Hands-on experience delivering production LLM-based solutions: agents, assistants, RAG

pipelines, or AI workflow automation.

• Proven Power BI development experience, including semantic modeling, DAX, and Power

Query.

• Strong Python and SQL skills.
• Ability to work autonomously, prioritize across a mixed AI/BI backlog, and communicate

clearly with non-technical stakeholders. - Experience embedding AI capabilities into BI tools (e.g., AI-generated narratives or insights

in dashboards).

• Familiarity with agentic AI patterns such as tool/function calling, memory and context

management, orchestration workflows, and MCP-based integrations.

• Familiarity with the Microsoft data platform: Fabric, Synapse, Purview.
• Familiarity with enterprise platforms such as ServiceNow, Salesforce, or Dynamics 365, and

system integration patterns.

• Experience with AI evaluation, monitoring, and responsible-AI practices.