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ZeyadKhalil

Agentic AI · RAG Pipelines · Data Systems · LLMs · ML Engineering

ZeyadKhalil

Building production-ready AI systems and intelligent pipelines.

Building AI systems and RAG pipelines that ship to production, including an embeddings based job matching copilot with semantic retrieval and full API orchestration, and a real time LLM data loss prevention platform. My work spans model development and evaluation, data pipelines, API engineering and cloud deployment across GCP and AWS. Currently completing MSc Applied AI at the University of Warwick (WMG) with an industry linked dissertation at Dogtooth Technologies.

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Featured work

Projects

Machine learning, analytical systems, LLM applications and production-focused software.

All projects
AI Systems · Sensor ML · Industry Research2026

Dogtooth AI Collision Intelligence System

MSc industry dissertation with Dogtooth Technologies. A sensor-driven pipeline that detects harmful infrastructure interactions on autonomous strawberry harvesting robots, reducing downtime without compromising safety.

Python · Sensor ML · Time-series features · Anomaly detection · Severity classification

In progress
LLM Security · Data Loss Prevention · Enterprise AI Security2026

PromptGuard AI: Enterprise LLM Data Loss Prevention

Applied AI security platform built during the WMG / Google / NatWest Secure Intelligence Frontier hackathon. Intercepts prompts sent to public LLMs from the browser and detects sensitive data leakage in real time. Chrome Extension (Manifest V3) for in-browser interception, FastAPI backend on Google Cloud Run for detection and policy enforcement, and a React admin dashboard for analytics and rule configuration.

FastAPI · Cloud Run · Chrome Extension MV3 · LLM classification · React dashboard

Active
Sports Analytics · Data Engineering · Analytical Systems2026

NBA Analytics Assistant

Offline Python analytics system that maps supported basketball questions to validated pandas tools, calculates auditable team statistics and returns structured answers through a modular parser, validator and registry pipeline.

Python · pandas · pytest · Data validation · Analytical tools

Completed
Agentic AI · Semantic Search · Full-Stack Product2025

Agentic AI Job Application Copilot

End-to-end automation platform that finds, ranks and helps apply to relevant graduate roles. FastAPI + SQLAlchemy 2 backend with APScheduler-driven Greenhouse scrapers, an embeddings-based semantic matching pipeline that ranks roles against a candidate CV, a Next.js 15 frontend with TanStack Query, and a 28-test suite locking in scraper reliability and matching logic.

FastAPI · Next.js 15 · Embeddings · SQLAlchemy 2 · Pytest suite

Active

Skills

Tools I actually use

Core technologies across my AI and software engineering work.

AI & Machine Learning

  • PyTorch
  • scikit-learn
  • NumPy
  • pandas
  • Supervised & unsupervised learning
  • Predictive modelling
  • Feature engineering
  • Model evaluation
  • Hyperparameter tuning
  • Data visualisation
  • Reinforcement learning

Backend, APIs & Data

  • FastAPI
  • Flask
  • SQLAlchemy
  • Data validation & quality
  • API design & integration
  • MySQL
  • PostgreSQL
  • SQL design & normalisation
  • ETL & data pipelines
  • Automated testing with Pytest

LLMs, RAG & Agentic AI

  • RAG (BM25 + embeddings)
  • Retrieval pipeline design
  • RAG evaluation & observability
  • Agentic workflow design
  • Embeddings-based semantic matching

Deep Learning, CV & Generative

  • Neural network training and evaluation
  • Transfer learning
  • Image classification
  • CycleGAN
  • Augmentation pipelines
  • Grad-CAM

Frontend & Full Stack

  • Next.js
  • React
  • TypeScript
  • Tailwind CSS

Languages & Programming

  • Python
  • JavaScript
  • Java
  • C++
  • C#
  • R
  • SQL

Spoken Languages

  • English
  • Italian
  • Arabic
  • French

Cloud, MLOps & Tooling

  • AWS
  • Google Cloud Platform
  • Docker
  • Git & GitHub
  • Linux command line
  • CI/CD workflows
  • Agile / Scrum

Contact

Open to AI, machine learning and software engineering opportunities.

I'm interested in roles where I can build production-focused AI systems, machine learning models, LLM applications, data pipelines and full-stack software for real users.