
Moiz
AI and Software Engineer for Web, Mobile, RAG and Backend Applications
Competenze

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Portfolio
Esperienza lavorativa
Software Developer
KNYSYS • Full time
Dec 2025 - Present • 9 mos
◦ Led the architecture and development of the UN Satellite Operator Management System, accelerating deployment cycles through GitHub Actions CI/CD while ensuring secure M2M communication through robust X-API key management. ◦ Designed a configurable Risk Analysis and Audit Trail System supporting 90% of declaration types, integrating a feedback loop to enhance accuracy, with automated alerts and end-to-end traceability through comprehensive audit logging. ◦ Developed a customizable Audit Workflow with configurable settings, dynamic task assignments, and escalation mechanisms using Prefect, enabling flexible business process automation and declaration verification
Full Stack Developer
InfraNext • Full time
Aug 2025 - Oct 2025 • 2 mos
* Improved database query performance by restructuring SQL joins and relationships, cutting average API response times from 450ms to under 200ms . * Created dynamic, user-centric UIs for data tables, submission forms, and profile/preferences modules, enhancing workflow clarity and significantly improving overall user experience. * Set up CI/CD pipelines to automatically run tests and deploy updates to production more efficiently. * Engineered an audit logging framework, and integrated Stripe and Shopify via REST/GraphQL pipelines to deliver multi-tenant onboarding, segregated billing workflows, and end-to-end order synchronization. * Created Automated and Manual Testing scripts to verify the workability and load testing of the system.
AI Engineer
NED University of Engineering and Technology • Part time
Jun 2024 - Nov 2024 • 5 mos
* Trained computer vision models for driver drowsiness, focus detection, and road segmentation, while scraping and collecting over 10,000+ road sign images for sign detection. * Created the Automated Pipeline for converting NoSql soil data to sql, interacts with the FPGA devices spread over the farming area which gives real-time insights of the soil condition. Then creates a real-time dashboard using folium and FastAPI. * Performed Manual testing of AI and Vision Models, testing for correct generations and responses.