Open to opportunities

Karim Gabr

@karimgabr

Message

Generative AI engineer building LLM agents, RAG systems, and ETL pipelines for scalable, production-ready solutions.

Egypt

Message

What I'm looking for

I’m looking for a role where I can build LLM agents and RAG applications end-to-end—owning ETL/data quality and deploying scalable services while continuously improving prompt and agentic workflows.

I’m a Computer Science graduate who has published research in Spiking Neural Networks and applied that curiosity to hands-on Generative AI engineering. I build production-ready LLM systems with a strong focus on relevance, reliability, and measurable impact.

As a Generative AI Engineer Intern at Saint Mary’s University, I built AlumAI, an LLM-powered alumni search agent serving 10,000+ records. Using advanced prompt engineering and RAG architecture, I improved query relevance by 40% and delivered production-grade data quality with 99% data integrity.

I also designed and deployed ETL pipelines with batch/stream processing and automated ingestion workflows, reducing data processing time by 35%. My work consistently paired model performance with disciplined data preprocessing, transformation, and validation for structured and unstructured datasets.

Before that, as a Software Engineer Intern at Ejada Systems, I implemented Spring Boot REST APIs with an Angular frontend supporting 500+ concurrent users. I automated data integration/cleaning/validation (cutting manual processing by 60%), optimized MySQL schemas and queries, and improved dashboard performance by 45%—the same engineering mindset I bring to LangChain/LangGraph and agentic workflows.

Experience

Work history, roles, and key accomplishments

Current

Project Manager

Current

Bit68

Feb 2026 - Present (3 months)

Managing the delivery of multiple digital products within a software house environment, leading cross-functional squads across backend, frontend, QA, and business roles. Serving as the primary bridge between clients and technical teams. Coordinating Agile workflows, removing blockers, and maintaining visibility over scope.

Project Management Jira Management Zoho CRM Zoho Software Development Lifecycle Software Sprint Planning Agile Methodologies Agile Development Agile Methodology Agile Project Management Client Relationship Management Client Communication Client Engagement client support

Generative AI Engineer Intern

Saint Mary’s University

Jul 2024 - Sep 2024 (2 months)

Built AlumAI, an LLM-powered alumni search agent for 10,000+ records, improving query relevance by 40% using prompt engineering and a RAG architecture. Designed and deployed ETL pipelines with batch/stream processing, reducing data processing time by 35% while ensuring 99% data integrity.

Prompt Engineering RAG LLM Agent Prompting ETL Batch Processing data preprocessing Vector Databases Data Validation

Software Engineer Intern

Ejada Systems

Jun 2023 - Aug 2023 (2 months)

Implemented Spring Boot REST APIs with an Angular frontend supporting 500+ concurrent users for secure, scalable enterprise applications. Automated data integration/cleaning/validation pipelines and optimized MySQL queries, reducing manual processing by 60% and improving dashboard performance by 45%.

Spring Boot REST APIs Angular MySQL Query Optimization Data Pipelines Data Cleaning SQL

Education

Degrees, certifications, and relevant coursework

German University in Cairo (GUC)

Bachelor of Science (B.Sc.), Computer Science Engineering

2020 - 2025

Activities and societies: Relevant coursework: Data Science, Machine Learning, Deep Learning, Computer Vision, Generative AI, Statistics, Distributed Systems. Thesis: Spiking CNNs for Video Classification; Publication: Spiking Convolutional Architecture for Action Recognition (IEEE ITC 2025).

B.Sc. in Computer Science Engineering at the German University in Cairo, with coursework in data science, machine learning, deep learning, generative AI, and distributed systems. Completed a thesis on spiking CNNs for video classification and authored an IEEE publication on spiking convolutional architectures for action recognition.