Youssef – Python, React, AWS

An enterprise AI and data platform designed for Fortune 500 organizations in healthcare and other regulated industries to process, analyze, and automate large-scale clinical and operational workflows. The platform combined AI capabilities, large language models, and scalable data pipelines to improve operational efficiency, accelerate content processing, and support secure, high-volume production environments.

Pfizer & Merck – AI Document Processing Platform

• Client & Stakeholders: Partnered with Pfizer and Merck regulatory affairs and medical writing teams, working directly with both technical stakeholders (data science, IT) and non-technical stakeholders (compliance, legal, medical writers) to align on requirements and review cycles.
• Business Problem & Ambiguity: Legal and regulatory document creation was manual, slow, and inconsistent across teams, with no clear standard for how AI-generated drafts should be reviewed and approved before use.
• End User: Medical writing and regulatory review teams responsible for producing and validating official documents.

Carbon Disclosure Project (CDP)

• Client & Stakeholders: Worked with CDP's data operations team in the UK, engaging technical stakeholders on pipeline design and business stakeholders on processing timelines and reporting needs.
• Business Problem & Ambiguity: High-volume questionnaire processing was slow and synchronous, creating bottlenecks during peak submission periods with no clear path to scale.
• End User: Internal data operations and analytics teams relying on timely questionnaire processing.

Saint-Gobain

• Client & Stakeholders: Collaborated with Saint-Gobain's engineering and data teams in France, working across technical stakeholders on architecture and platform requirements.
• Business Problem & Ambiguity: Needed scalable backend infrastructure and data pipelines to support enterprise-level distributed workloads, with requirements evolving as system scale grew.
• End User: Internal engineering teams and downstream applications consuming the data pipelines.

Pfizer & Merck AI Document Processing Platform

• Designed and developed a collaborative AI platform for generating and reviewing legal and regulatory documents, partnering with medical writing, compliance, and regulatory affairs stakeholders across Pfizer and Merck.
• Built human-in-the-loop review workflows enabling medical writing teams to generate, review, and approve documents efficiently, replacing manual, inconsistent review processes.
• Built CI/CD pipelines and deployment automation across the Pfizer and Merck engagements, reducing deployment time by 40%.

CDP Questionnaire Processing Optimization

• Built a microservices architecture powering multiple platforms for both client-facing and back-office use, supporting questionnaire generation and distribution across services.
• Designed and built a questionnaire editor enabling teams to create and manage questionnaires.
• Optimized high-volume questionnaire processing using Kafka-based asynchronous pipelines, reducing processing time by 86%, from 15 minutes to 2 minutes.
• Collaborated with data science to build and integrate an ML model for scoring questionnaires.

ApoBank Loan Document Processing Platform

• Designed and developed a document processing platform for ApoBank Germany to extract data from corporate loan applicant documents, working with loan officers and credit analysts to define requirements.
• Built extraction and search capabilities allowing users to quickly locate and verify specific information within unclear or inconsistently formatted client documents, supporting faster loan approval/rejection decisions.

Saint-Gobain AI Product Search & Quote Generation

• Designed and implemented an AI-powered platform enabling Saint-Gobain agencies to search for products and generate customer quotes quickly, replacing slower manual lookup and quoting processes.
• Built scalable backend services and distributed data pipelines using Python, FastAPI, Java Spring Boot, Kafka, SQL/NoSQL, Docker, and Kubernetes to support the platform.

A digital finance platform built for the African market, focused on security, scalability, and reliability across the full payment lifecycle. The system handled high-stakes financial transactions and required strict compliance with security standards.

• Developed high-quality object-oriented software for the finance sector with a focus on security and scalability
• Built and deployed backend services using Java Spring Boot and Python, integrated with RabbitMQ for async messaging
• Implemented authentication and authorization using Keycloak across multiple services
• Developed frontend interfaces using React.js, improving user experience for digital payment workflows
• Managed deployments using Docker and Linux environments, ensuring reliable and consistent delivery
• Contributed across the full SDLC — from requirements through testing and production deployment
• Improved backend reliability and deployment consistency through Docker, Linux environments, and CI/CD pipelines.

A full-stack web application designed for a startup to improve user engagement, streamline team collaboration, and enable real-time notifications. The platform provides a centralized environment for communication and task coordination, helping teams collaborate more efficiently and stay informed through instant updates.

• Designed and developed a notification system to improve user engagement.
• Built backend services using Java Spring Boot connected to a MySQL database.
• Developed frontend components using Angular, translating business requirements into functional user interfaces.
• Helped introduce Agile/Scrum practices, including daily standups, sprint backlogs, planning sessions, and delivery tracking.
• Participated across the SDLC, including development, testing, bug fixing, and software delivery.

A Java-based web application developed in an enterprise training environment to demonstrate core backend development concepts and modern web application architecture. The project focused on applying Core Java, object-oriented programming principles, and fundamental web development practices in a realistic enterprise workflow.

• Developed Java web application features using Core Java and object-oriented programming principles.
• Implemented basic frontend and backend functionality for enterprise-style applications.
• Collaborated with team members to design, build, and test Java-based web solutions.