Building Agentic Workflows and RAG Architectures at the intersection of Data Science & Engineering
The tools and frameworks I use to build intelligent systems.
RAG (Hybrid Search), LangGraph, LLMs, Model Context Protocol (MCP), Agentic Frameworks.
Neo4j (Graph), Qdrant, Snowflake, Databricks, MongoDB, SQL Server.
Python, SQL, PySpark, PyTorch, Scikit-learn, Pandas, FastAPI.
Selected work demonstrating real-world AI impact.
FastAPI • LangGraph • Qdrant
Designed an autonomous ReAct agent loop that refines queries to identify top subject-matter experts instantly.
Azure • GenAI Agents
Led an agent-powered system for contract analysis, reducing manual KPI review effort by 80-90%.
Telecom ML • Sklearn
Built a roaming use-case model for a major telecom client, achieving a 50% uplift in conversion rates.
Neo4j • Text-to-Cypher
Engineered a pipeline allowing natural language queries on graph data, saving 10 hours/week for stakeholders.
Where I've shaped intelligent systems and driven impact.
AI Engineer
Technology Consultant
Industry-recognized credentials validating my expertise.
Azure AI Fundamentals
Microsoft • 2026
Azure Data Fundamentals
Microsoft • 2023