Agentic AI Engineer

Skills & Tools

•     Hands-on agentic AI / LLM engineering: building and operating MCP servers, agent workflows, prompt design, and output validation.

•     REST API integration: Microsoft Fabric, Power BI, Tableau Server, SSRS, Azure DevOps, Azure Resource Manager.

•     Code analysis tooling: SQL parsing, PySpark/DAX comparison, NLP-based semantic similarity, dependency graph construction.

•     Strong SQL and Python; Git repository automation.

Experience: 5+ years data engineering or platform automation; 1–2+ years hands-on LLM/agentic systems (MCP, agent frameworks) in production or client-delivery settings.

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IVY