Mohamed Abu Fareed M — AI Researcher

I am an AI Engineer at MathCo specializing in Generative AI, Large Language Models (LLMs), and multi-agent systems for enterprise applications. I design and build production-ready AI solutions that combine LLM reasoning, structured data retrieval, and tool orchestration to deliver reliable, scalable, and business-critical intelligence systems. My work centers on developing LLM-powered conversational systems that understand intent, perform dynamic tool selection, and execute complex workflows - including Text-to-SQL, document intelligence, hypothesis validation, and automated executive summarization. I have built and deployed AI agents that translate natural language into structured queries, extract knowledge from unstructured documents, and generate contextual business insights over large enterprise datasets. Across industries (pharma, consumer healthcare, and oil & gas), I have delivered end-to-end AI solutions: * Designed and optimized Text-to-SQL and Text-to-Definition agents for a U.S. pharmaceutical client, focusing on accuracy, latency, and reliability. * Built an enterprise chatbot capable of generating complex multi-table SQL queries with contextual reasoning over large-scale data. * Applied LLMs, OCR post-processing, and structured extraction pipelines to digitize and analyze handwritten refinery reports from the 1960s–70s. Currently, I am developing a Retailer SRM Copilot - a multi-agent AI system integrating: * Text-to-SQL for structured analytics * Document intelligence for policy and knowledge retrieval * Hypothesis agent for trend validation and root-cause reasoning * Executive summary agent for KPI-driven narratives This system is embedded directly into Power BI to enable natural-language analytics and automated insight generation. On the engineering side, I build scalable AI backends using FastAPI, design system architectures for enterprise AI deployments, and optimize data pipelines for performance and reliability. I have hands-on experience with Gemini 2.5 Pro, GPT-4o, GPT-4.1, GPT-o3, GPT-o3-mini, GPT-5/5.1, prompt engineering, retrieval-augmented generation (RAG), and agentic workflows. I am passionate about advancing LLM systems from prototypes to production, ensuring robustness, observability, and measurable business impact.

Stackforce AI infers this person is a Generative AI Engineer specializing in enterprise applications and multi-agent systems.

Location: Bengaluru, Karnataka, India

Experience: 2 yrs 5 mos