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Generative AI Engineer with 1+ years in AI Systems & RAG Pipelines
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Assessing your cultural and operational fit
Generative AI & ML Engineer with 2+ years of experience building production-ready AI systems, LLM applications, RAG pipelines. Specialized in designing multi-agent workflows using LangGraph and CrewAI, fine-tuning models with LoRA/QLORA, and deploying scalable solutions via Docker and CI/CD pipelines to deliver measurable impact across real-world.
Tanta Higher Institute of Engineering
Bachelor's Degree · Telecom Engineering
N/A – June 30, 2026
SEG
Generative AI Engineer
April 1, 2026 – Present
Al Manşūrah, Dakahlia Governorate, Egypt
Freelance / Self-employed
AI & Agentic Systems Developer
January 1, 2025 – June 1, 2026
Shibīn al Kawm, Monufia Governorate, Egypt
Agent Engineering Team
March 1, 2026 – June 1, 2026
Built multi-agent AI pipeline using LangGraph and Gradio that transforms a plain-text idea into a production-ready React + FastAPI application automatically. Orchestrated 7 specialized agents powered by Llama-3.3-70B and GPT-40 Mini, utilizing prompt engineering. Implemented self-evaluation loop with static analysis and LLM scoring, ensuring high code quality before output.
Multi-Agent Research Assistant
December 1, 2025 – June 1, 2026
Built autonomous multi-agent system using LangGraph for automated research and report generation. Integrated Wikipedia API, and Python REPL with a self-critique loop and async support to high-quality LLM evaluation. Automated 80% of research workflows, delivering 20+ reports with 95% user satisfaction.
AI Predictive Maintenance System
June 1, 2025 – November 1, 2025
Built predictive model achieving 97.8% accuracy in forecasting equipment failures, utilizing MLflow for tracking. Integrated YOLOv5 for real-time defect detection with RAG support for technical manual retrieval. Deployed production-ready solution with FastAPI and SHAP, cutting operational downtime by 40%.
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with cutting-edge AI development, particularly in agentic systems and RAG. The diversity of projects, from predictive maintenance to automated research and code generation, shows adaptability and a broad interest within the AI domain. The freelance experience indicates initiative and self-management. The ongoing internship and recent graduation suggest a candidate eager to learn and contribute, which generally aligns well with a dynamic, innovation-focused culture. However, the limited professional experience (internship and freelance) means cultural fit in a larger corporate environment is yet to be fully proven.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong problem-solving aptitude and an ability to deliver practical, high-impact solutions. The focus on multi-agent systems and autonomous workflows suggests an innovative and self-directed approach. The use of self-evaluation loops and static analysis points to a commitment to quality and robust system design. However, without direct assessment data, specific soft skills like teamwork, communication, and stress handling cannot be definitively evaluated.