AI Engineer · Open to opportunities

I engineer intelligent systems for complex business problems.

I’m Usman Jadoon. I’m an AI Engineer with 3+ years of experience spanning enterprise data analytics and AI engineering, specializing in Agentic AI, Multi-Agent Systems, LLM applications, RAG, AI orchestration, and Python backend development.

ACTIVE SYSTEM UJ / 2026
RETRIEVAL
REASONING
ORCHESTRATION
AGENTIC AI
Multi-Agent Evaluated Production-oriented
AGENTIC AI MULTI-AGENT SYSTEMS LLM APPLICATIONS RAG LLM ROUTING ORCHESTRATION PYTHON FASTAPI AI EVALUATION AGENTIC AI MULTI-AGENT SYSTEMS LLM APPLICATIONS RAG LLM ROUTING ORCHESTRATION PYTHON FASTAPI AI EVALUATION

/ WHAT I DO

From intelligent models to production-oriented AI systems.

My work sits at the intersection of AI engineering, data science, backend development, and enterprise analytics.

01

Agentic AI & Multi-Agent Systems

Designing specialized AI agents and orchestration workflows for complex reasoning, data analysis, retrieval, validation, and tool execution.

02

RAG & knowledge systems

Building hybrid retrieval systems using vector search, dense and sparse retrieval, reranking, and evaluation to ground LLM responses in enterprise knowledge.

03

AI Product Engineering

Building end-to-end AI platforms with Python, FastAPI, LLM routing, Text-to-SQL, APIs, data pipelines, evaluation, observability, and workflow automation.

/ SELECTED WORK

Systems engineered for complex problems.

All projects
01

Autonomous AI Data Analyst Platform

A production-oriented autonomous AI data analyst platform combining multi-agent orchestration, Text-to-SQL analytics, statistical analysis, cross-modal RAG, LLM routing, and automated executive reporting.

AGENTIC AI LANGGRAPH TEXT-TO-SQL LLM ROUTING
02

Enterprise Multi-Agent RAG Platform

A 12-layer Agentic AI platform combining hybrid retrieval, AST-guarded Text-to-SQL analytics, dynamic LLM routing, AI safety guardrails, workflow automation, and production observability.

MULTI-AGENT RAG HYBRID RETRIEVAL LLM ROUTING AI EVALUATION
03

AI & Machine Learning Applications

Applied AI and machine learning projects spanning a GPT-3.5 RAG e-commerce chatbot, predictive analytics, time-series forecasting, and T5 Transformer-based text summarization.

RAG NLP TRANSFORMERS MACHINE LEARNING

/ HOW I THINK

“The goal is to engineer AI systems that can reason, retrieve, act, and deliver results people can trust, understand, and use.
01Design for scale and reliability
02Ground outputs in evidence
03Measure what matters
04Ship, observe, improve

/ NEXT

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