Fateen Ahmed

Fateen Ahmed

AI Engineer • Simulation Engineer • M.S. Artificial Intelligence

Professional Overview

I am an AI Engineer with experience in intelligent agent systems, simulation modeling, and generative AI applications. Having completed my M.S. in Artificial Intelligence at the Illinois Institute of Technology, I focus on developing practical AI solutions that address real-world industrial challenges.

In my role as a Simulation Engineer at Amazon, I design and implement large-scale discrete event simulations for fulfillment center optimization. My work combines academic knowledge with practical application, developing agentic AI systems that enhance operational efficiency and decision-making processes in complex logistics environments.

Areas of Expertise

Agent-Based Systems

Development of intelligent agent architectures using CrewAI and AutoGen for automated problem-solving and collaborative decision-making in enterprise environments.

Simulation Engineering

Design and implementation of discrete event simulations for complex operational systems, with focus on logistics optimization and throughput analysis.

Retrieval-Augmented Generation

Implementation of RAG systems with vector databases for automated document analysis and knowledge extraction from technical specifications.

GenAI Applications

Development of generative AI solutions using large language models, with applications in business process automation and data analysis.

Professional Experience

Simulation Engineer
Amazon, Bellevue, WA
November 2024 - Present

Architect discrete event simulations for fulfillment center operations, modeling within-yard and off-yard processes to optimize throughput and evaluate system retrofits. Develop agentic AI solutions using RAG and AWS Bedrock Agents for automated analysis of vendor proposals and comprehensive test plan generation using large language models.

Software Engineer - GenAI
Byanat, Muscat, Oman
May 2024 - October 2024

Developed AI-driven data catalog applications leveraging LLMs for intelligent search, insights, and visualizations. Researched agentic approaches for automated data analysis and created observability dashboards with integrated LLM-based graph generation using LIDA.

Research Participant - Meta Llama Challenge
Meta, Dubai, UAE
September 2024 - October 2024

Collaborated with RTA Dubai to develop innovative solutions for public transport optimization. Built a comprehensive mobility data analytics platform integrating GTFS analysis, sentiment analysis, and large language models for route planning insights. Implemented tool-calling mechanisms with LangChain for automated query processing and traffic pattern analysis.

Education

Master of Science in Artificial Intelligence
Illinois Institute of Technology, Chicago, IL
August 2023 - May 2025
Bachelor of Engineering in Computer Engineering
National University of Science and Technology, Oman
September 2019 - June 2023

Technical Competencies

AI/ML Frameworks

LangChain, AutoGen, CrewAI, TensorFlow, PyTorch, Transformers, LIDA

Cloud & Infrastructure

AWS Bedrock, Vector Databases, FastAPI, Docker, Kubernetes

Programming Languages

Python, JavaScript, C++, SQL, R

Specialized Tools

Discrete Event Simulation, GTFS Analysis, Text2SQL, Data Visualization

Key Projects & Applications

Amazon Fulfillment Center Simulation Engine
Discrete event simulation system for modeling warehouse operations, retrofit evaluation, and throughput optimization across multiple facilities
Agentic AI Test Planning System
RAG-powered application using AWS Bedrock Agents for automated vendor proposal analysis and comprehensive test strategy generation
GenAI Mobility Analytics Platform
Transportation data analysis system using Llama models for GTFS processing, interactive visualization, and route optimization insights
LLM-Integrated Observability Dashboard
Real-time analytics platform with automated graph generation using LIDA, enabling dynamic data visualization and insights extraction
AI-Generated Content Detection System
Machine learning pipeline for identifying synthetic content in e-commerce reviews using advanced natural language processing techniques