I'm an AI Engineer with 1+ year of professional experience building AI-powered applications, Generative AI solutions, and backend systems.

My work focuses on transforming AI concepts into practical applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, NLP, Machine Learning, vector databases, and backend APIs.

I enjoy working across the complete AI application lifecycle — from data processing and model integration to retrieval, API development, business logic, deployment, and evaluation.

• 🤖 Building Generative AI & Agentic AI applications
• 🧠 Working with LLMs, RAG, embeddings & NLP
• 🔎 Building semantic retrieval using Qdrant & FAISS
• ⚡ Developing AI backend services with FastAPI & Flask
• 🔗 Integrating LLMs, APIs, tools & databases
• 🐳 Containerizing AI applications using Docker
• 📊 Strong foundation in Machine Learning & Data Science
• 🧪 Focused on AI evaluation, reliability & production readiness
• 🚀 Exploring advanced Agentic AI & enterprise AI architectures
• 📍 Based in the UAE

• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• AI Agents & Agentic Workflows
• Prompt Engineering
• Tool / Function Calling
• Embeddings & Semantic Search
• Vector Databases
• NLP & Text Classification
• Document Intelligence
• Conversational AI
• AI Automation
• Machine Learning
• Model Evaluation

Python • R • SQL • JavaScript • HTML • CSS

PyTorch • TensorFlow • Scikit-learn • Transformers • SentenceTransformers • spaCy • NLTK • Pandas • NumPy

LLMs • RAG • AI Agents • Prompt Engineering • Embeddings • Function Calling • Tool Integration • OpenAI • Gemini • Groq • Ollama

FastAPI • Flask • REST APIs • API Integration • JSON • Async Python

MySQL • Qdrant • FAISS • Vector Search

Docker • Git • GitHub • VS Code • Linux • Nginx • Gunicorn

Production-focused NLP classification system combining traditional machine learning with semantic sentence embeddings.

• ⚡ FastAPI prediction service
• 🧠 MiniLM sentence embeddings
• 📊 Logistic Regression classification
• 🔬 TF-IDF baseline comparison
• 📈 ~95% held-out classification accuracy
• 🤖 Low-confidence LLM fallback
• 🐳 Dockerized application
• 🧪 Automated testing
• 📊 Model evaluation & error analysis

Tech: Python FastAPI MiniLM Scikit-learn Docker LLM APIs

AI-powered assistant designed around agent-style workflows, LLM integration, and backend APIs.

• AI agent workflows
• LLM-powered reasoning
• API integration
• Backend orchestration
• Practical AI automation

Tech: Python FastAPI LLMs AI Agents REST APIs

➡️ View TechMate Repository

Retrieval-Augmented Generation application designed to answer questions using external knowledge sources.

Documents
    ↓
Processing / Chunking
    ↓
Embeddings
    ↓
Vector Database
    ↓
Semantic Retrieval
    ↓
LLM
    ↓
Grounded Response

Tech: Python FastAPI Qdrant FAISS Embeddings LLMs

AI-powered educational document system for transforming learning materials into structured educational content.

• 📄 PDF processing
• 📚 Study-plan generation
• 📝 Syllabus generation
• ❓ MCQ generation
• 🤖 LLM-powered content generation
• 🔎 Document retrieval

Tech: Python Flask LLMs RAG Qdrant

Conversational AI solution designed around banking customer-support use cases.

• Arabic & English conversational AI
• LLM-powered customer assistance
• Knowledge retrieval
• Banking-oriented AI workflows
• Multilingual NLP

Tech: Python LLMs RAG NLP Vector Search

Enterprise-oriented AI document intelligence solution focused on extracting, understanding, and retrieving information from organizational documents.

• Enterprise AI
• Document Intelligence
• Retrieval-Augmented Generation
• Semantic Search
• LLM Integration

Tech: Python RAG LLMs Vector Databases Document Processing

AI-powered wellness assistant combining conversational AI with structured health and activity information.

• Conversational AI assistant
• Wellness logs
• Personalized recommendations
• Data visualization
• Chat history
• Voice interaction

Tech: Python Streamlit Ollama LLMs Speech Recognition

I focus on the complete AI application, not only the model.

┌─────────────────────────┐
│ User / Business Request │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│      API / Backend      │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│ Intent / Agent Workflow │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│ Retrieval / Tools / API │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│ Vector DB / Data Source │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│           LLM           │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│ Validation / Evaluation │
└────────────┬────────────┘
             ↓
┌─────────────────────────┐
│     Final Response      │
└─────────────────────────┘

My focus is on building systems that are:

Reliable • Grounded • Maintainable • Scalable • Observable • Production-Ready

I'm currently deepening my knowledge and practical experience in:

🤖 Agentic AI Systems
🧠 LLM Application Engineering
📚 Advanced RAG Architectures
🔗 AI Agent Tool Integration
⚡ Production FastAPI Backends
🔎 Vector Search & Retrieval
🧪 LLM & RAG Evaluation
🐳 AI Application Deployment
🔐 AI Guardrails & Reliability
📊 AI Observability

Building an AI demo is only the beginning. The real engineering challenge is creating AI systems that remain reliable with real users, real data, and real business requirements.

I focus on bridging the gap between AI models and production applications by combining AI engineering, backend development, retrieval systems, APIs, databases, evaluation, and deployment.

I'm interested in opportunities involving:

AI Engineering • Generative AI • LLM Applications • RAG • Agentic AI • NLP • AI Backend Engineering

Thanks for visiting my profile! 🚀