Open to opportunities

Albaraa Taher Zeinoglu

@albaraataherzeinoglu

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Fullstack developer building production SaaS and mobile AI apps; I lead end-to-end architecture and delivery.

Turkey

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What I'm looking for

I want to work in a fast-paced product team building AI-powered mobile applications at scale. I’m eager to own end-to-end architecture and delivery, and to mentor junior developers while advancing the technical quality of the team.

I’m a Computer Engineering graduate from METU with hands-on fullstack development experience across web, mobile, and embedded systems. I’ve built production SaaS platforms using React, Node.js, and .NET, with a strong focus on RESTful API design and real-time systems.

At Fornax, I maintain and extend Restra, a multi-tenant SaaS restaurant POS serving restaurant chains across 9+ countries. I built a React/TypeScript back-office portal, a .NET 10 backend with Clean Architecture, Entity Framework Core, PostgreSQL, and SignalR, and integrated the Odeal QR-code payment gateway via a standalone Node.js/Express adapter.

Previously at AtomiCoat, I developed a Flutter/Dart industrial IoT app to control Atomic Layer Deposition machines on iOS and Android. I engineered a Raspberry Pi backend integrating with PLCs via Modbus TCP, created React/TypeScript dashboards with live sensor visualization, and built a Python physics-based virtual machine with 200+ unit and integration tests (pytest).

I’m excited to join a fast-paced product team creating AI-powered mobile applications at scale. My eventual goal is to lead the development of innovative software products—taking ownership of end-to-end architecture and delivery while mentoring junior developers and contributing to the technical growth of the team.

Experience

Work history, roles, and key accomplishments

Current

Fullstack Developer

Current

Fornax

Nov 2025 - Present (7 months)

Maintained and extended Restra, a multi-tenant SaaS restaurant POS platform serving 9+ countries. Built a React/TypeScript back-office portal and a .NET 10 backend using Clean Architecture, Entity Framework Core, PostgreSQL, and SignalR for real-time order updates.

React TypeScript Tanstack Query Clean Architecture Entity Framework PostgreSQL SignalR Redux

Fullstack Developer Intern

Fornax

Sep 2025 - Nov 2025 (2 months)

Designed and prototyped the initial POS application interface for restaurant order and payment management from the ground up. Connected restaurant operations with Odeal POS hardware by implementing the payment gateway API integration.

React TypeScript Payment Integration API Integration Odeal Integration Frontend Development

Software Developer

Teogen

Jun 2025 - Aug 2025 (2 months)

Programmed an Electron/React desktop application to control Peltier cooling systems on textile testing machines via Modbus TCP. Implemented PID, adaptive PID, and neural model predictive control algorithms, built a Flutter mobile app for on-site testing, and coordinated Supabase integration for test data synchronization and Excel report generation.

Electron React Modbus PID Controller Model Predictive Control Flutter Supabase Excel reporting

Mobile App Developer & Intern Supervisor

AtomiCoat

Oct 2024 - Aug 2025 (10 months)

Developed a Flutter/Dart application from scratch to control industrial Atomic Layer Deposition (ALD) machines, deployed on iOS and Android. Engineered a Raspberry Pi backend integrating with PLCs via Modbus TCP, created React/TypeScript live monitoring dashboards, produced a Python physics simulator with 200+ unit/integration tests, and supervised 6 interns during summer 2025.

Flutter Dart Raspberry Pi Modbus React TypeScript Recharts Python Pytest

Mobile App Developer Intern

AtomiCoat

Sep 2024 - Present (1 year 9 months)

Onboarded onto the ALD machine control project, learning Flutter/Dart and industrial IoT protocols. Prototyped the initial mobile app interface for Atomic Layer Deposition equipment monitoring.

Flutter Dart IoT Protocols ALD Equipment Monitoring iOS Development Android Development

Machine Learning Intern

Solar Biotec

Developed computer vision models for blood type analysis using gel card readers and applied deep learning for medical diagnostic equipment automation. Contributed to healthcare technology solutions using MEMS and sensors.

Deep Learning Computer Vision Blood Type Analysis Medical Diagnostic Automation MEMS Sensors Sensor Integration Model Development Evaluation

Education

Degrees, certifications, and relevant coursework

Middle East Technical University (METU NCC)

Bachelor of Science in Computer Engineering, Computer Engineering

2021 - 2026

B.S. in Computer Engineering at METU’s Northern Cyprus Campus (expected completion June 2026). Coursework includes Data Structures, Algorithms, Computer Networks, Deep Learning, System Simulations, and Design Patterns.