Available to hire
I’m Zain Ul Abdin, a results-driven Lead Software Developer focused on building end-to-end, high-performance web and mobile apps. With 3+ years of experience, I leverage React, React Native, and cloud-native AWS Serverless architectures to deliver scalable SaaS and industrial monitoring platforms.
I’m passionate about architecting full-stack solutions using Node.js and Python to drive measurable business impact, and I love crafting intuitive UI/UX. I enjoy mentoring teams, elevating code quality through CI/CD, and exploring AI-assisted development to accelerate delivery cycles.
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Language
English
Fluent
Work Experience
Lead Full-Stack Developer at Reon Energy Limited
September 30, 2022 - PresentActed as Subject Matter Expert for a global industrial monitoring platform, leading cross-functional teams to build high-availability solutions for international markets. Engineered real-time anomaly detection systems and automated workflows that improved site uptime by 5% and reduced operational maintenance visits by 40%. Architected Node.js APIs and AWS Serverless microservices to ingest and process real-time data from 7,000+ globally distributed IoT devices. Led the development of high-performance React dashboards and a React Native mobile ecosystem, resulting in a 10% increase in asset utilization for enterprise clients. Established high-quality code standards via rigorous code reviews and CI/CD pipelines, while mentoring junior engineers in an Agile environment.
Software Engineer Intern at Semper8
April 30, 2025 - July 31, 2025Full-stack MI Architecture: developed an interview analytics platform featuring a React.js web application, a Node.js orchestration layer, and a Python (Flask) backend for high-performance ML processing. Computer Vision & Verification: architected real-time face detection and recognition workflows using OpenCV, achieving >90% accuracy in automated identity verification during live interviews. NLP & Sentiment Analysis: integrated OpenAI, Whisper (STT), and VADER to automate speech-to-text processing and sentiment analysis, extracting emotional tone and response correction for scoring. Cloud Infrastructure: designed RESTful APIs secured with AWS Cognito; managed scalable deployment using AWS Elastic Beanstalk and NGINX. Process Automation: improved operational efficiency by 40% by fully automating data ingestion and ML inference pipelines, reducing manual processing time significantly.
Education
Master of Applied Computing at University of Windsor
May 1, 2024 - August 31, 2025Bachelor of Computer Systems Engineering at NED University of Engineering & Technology
October 1, 2018 - October 1, 2022Qualifications
Industry Experience
Software & Internet, Professional Services, Manufacturing, Energy & Utilities
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