● Design and build retrieval-augmented generation (RAG) systems using embedding models, LLM APIs, LangGraph, and the Model Context Protocol (MCP). ● Developed an LLM-based extraction pipeline that transforms unstructured records into reliable, schema-validated structured output, with a focus on output faithfulness and reliability. ● Engineer prompt strategies and structured-output constraints for production LLM workflows, improving consistency and reducing malformed responses. ● Build and maintain backend services in .NET / ASP.NET Core (C#) supporting AI-powered features. ● Evaluate embedding and retrieval quality to align model behaviour with product and accuracy requirements.

● Led product development and launch initiatives for 5.5G solutions, achieving up to 5 Gbps downlink throughput for national telecom clients. ● Coordinated cross-functional teams across engineering, marketing, and supply chain to deliver large-scale network projects on schedule and within budget. ● Prepared and presented technical proposals, solution designs, and performance reports to executive stakeholders.