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Internship : Leveraging AI for Frontend Modernization at ELCA Global Career site

Pully, Vaud, Switzerland -

Full Time

Start Date

Immediate

Expiry Date

22 Feb, 26

Salary

0.0

Posted On

24 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computer Science, .NET, Web API, TypeScript, React, Vue.js, AI Engines, Analytical Skills

Industry

IT Services and IT Consulting

Description

Description This internship focuses on the migration of a Single-Page-Appliction’s frontend technology . Previous projects within the organization have approached similar migrations through fully manual code rewriting, which, while effective, proved time-consuming and resource-intensive. The aim of this internship is to evaluate whether an AI-driven migration approach can provide tangible benefits compared to traditional manual migration. By leveraging modern AI tools and frameworks, the project will investigate the efficiency, reliability, maintainability, and overall viability of automated support in technology migration. Objectives Evaluate AI-driven code migration tools and methodologies Benchmark AI-assisted migration against manual migration Propose best practices for future migrations Our offer A dynamic work and collaborative environment with a highly motivated multi-cultural and international sites team The chance to make a difference in peoples’ life by building innovative solutions Various internal coding events (Hackathon, Brownbags), see our technical blog Monthly After-Works organized per locations Skills required Computer Science student, very good analytical skills Programming skills: .NET, Web API, TypeScript, React, Vue.js Knowledge and experience of different AI engines This internship starts in February 2026. Applications must include your most recent academic transcripts (grades); applications without transcripts will not be considered.

Responsibilities

The internship focuses on evaluating AI-driven migration approaches for frontend technology. It aims to benchmark these methods against traditional manual migration techniques.