About Rana Umar
Passionate AI/ML Engineer transforming complex data into intelligent solutions
My Story
I am a GenAI Engineer & Python Developer dedicated to building the next generation of autonomous systems through Agentic AI, RAG architectures, and Voice Intelligence. My expertise lies in architecting intelligent agents that don't just process information, but actively reason and interact with their environment to solve complex tasks. I specialize in creating production-ready applications using LangChain and LangGraph, with a particular focus on Retrieval-Augmented Generation (RAG) to provide LLMs with specialized, real-time knowledge.
By integrating Voice Agents and automated data extraction pipelines, I bridge the gap between human interaction and machine intelligence to deliver seamless, context-aware user experiences. My work is grounded in a proficiency for Machine Learning workflows, ensuring that every agent is powered by clean, optimized data and robust predictive pipelines. I am committed to transforming raw data into sophisticated, agent-driven solutions that provide tangible business value and push the boundaries of what AI can achieve.
Technical Skills
My expertise spans across various domains in AI/ML, data science, and GenAI development.
Python
Primary language for GenAI development, Agentic workflows, and high-performance APIs.
LangChain
Orchestrating complex LLM chains and Retrieval-Augmented Generation (RAG) pipelines.
LangGraph
Building stateful, multi-agent autonomous systems with complex reasoning loops.
LangGraph
Building stateful, multi-agent autonomous systems with complex reasoning loops.
LiveKit
Design and develop real-time voice agents and interactive applications using LiveKit's WebRTC infrastructure.
RAG Architectures and Systems
Designing and implementing Retrieval-Augmented Generation (RAG) systems to enhance LLM capabilities with external knowledge sources.
Vector Databases
Implementing high-dimensional similarity search using FAISS, Pinecone, or ChromaDB.
FastAPI
Developing asynchronous, production-ready RESTful APIs for AI model deployment.
Docker
Containerizing AI applications to ensure consistent deployment across environments.
Scikit-learn
Machine learning algorithms, feature engineering, and predictive modeling.
Pandas & NumPy
Advanced data manipulation, cleaning, and numerical computing for ML pipelines.
Git & GitHub
Version control, CI/CD workflows, and collaborative software development.
Experience & Education
My professional development and academic journey
Professional Experience
Self Learning - GenAI Engineer
Self-directed learning in GenAI, focusing on RAG architectures, agentic AI, and voice agents. Gained hands-on experience with LangChain and LangGraph for building intelligent agents.
AI/ML Engineer - Internship
Practice in building Rag based systems, agentic AI, and voice agents. worked on projects involving LLM integration and data pipeline development
Applied AI Engineer - Junior
Experience in developing and deploying AI solutions, with a focus on RAG architectures and agentic systems. Proficient in using LangChain and LangGraph for building intelligent agents. Livekit based voice agent development and integration.
Education
Bachelor's in Computer Science
Specialization in Machine Learning and Data Science
ML & Data Science Certification
Advanced coursework in Machine Learning and Data Science
Ready to Work Together?
Let's discuss how I can help transform your data into actionable insights and intelligent solutions.