Sven Ahac

About me

I am a 25-year-old software developer with experience in developing web and mobile applications. I continuously expand my knowledge through personal projects and by exploring new technologies. I enjoy working on projects where I can combine technical knowledge, creativity, and teamwork. In my free time, I enjoy traveling and playing volleyball.

Work Experience

Front-End Developer

Calda

Nov 2025 – Current

  • Developed responsive web and mobile applications using Next.js, TypeScript, and Flutter
  • Implemented features and user interfaces based on client requirements and designs
  • Collaborated directly with clients to gather feedback and refine application functionality

QA Test Engineer

Abrantix d.o.o.

Mar 2025 – Jul 2025

  • Testing software on different POS terminals
  • Identifying and reporting software and hardware bugs
  • Fixing tests for automated testing

Teaching Assistant

Digital School

Oct 2024 – Jul 2025

  • Worked as a teaching assistant, helping children learn web development using HTML, CSS, and JS
  • Assisted with Python programming lessons

Full-Stack Developer

Aerio

Feb 2023 – Feb 2025

  • Occasional collaboration in a small startup
  • Front-end development in React.js with Typescript
  • Back-end development using Node.js and PostgreSQL

Projects

Magnetrip

A web and mobile application for storing and reliving travel memories using physical NFC-enabled fridge magnets. Each magnet is linked to a specific trip containing its photos and story. Users can simply tap the magnet with their phone to instantly access the trip without logging in.


Technologies used: Next.js, Supabase, TailwindCSS, shadcn/ui, Flutter

Digitalna Košarica

A Slovenian grocery price-comparison app. Users can compare prices across five major chains (Spar, Mercator, Hofer, Lidl, Tuš), build a shopping basket with live per-store subtotals, track price history per product and see loyalty-card discounts. I worked on designing and implementing the front-end part of the app.


Technologies used: Next.js, Typescript, TailwindCSS

The project is still an early, in-development version.

Urban noise classification annotator

Software made for my thesis. A web application in which the user can specify what they hear in intervals of an audio recording. These recordings will then be used to train a model for automatic recognition of audio files.


Technologies used: Svelte, Typescript, Express, TailwindCSS, Docker

Kernel Image Processing

Kernel Image Processing is an assignment for a school project. Core matrix image processing. The program is made sequential, parallel and distributed.


Technologies used: Java