Leverage and contribute to the development of GenAI and AI-powered tools to enhance development productivity
Collaborate effectively with international, multilingual teams across multiple time zones
Education: Currently enrolled in or completed a Bachelor's or Graduate degree in Computer Science, Software Engineering, Data Science, or a related STEM field (minimum 60 ECTS in programming, algorithms, and systems).
Expected graduation between October 2025 – September 2026, or graduated within the last 24 months.
Technical Requirements
Java: 1+ year hands-on experience developing applications, including object-oriented design patterns and the Java Collections Framework
Spring Framework: Experience with Spring Boot or Spring MVC, including dependency injection and RESTful API development
Data Structures & Algorithms: Practical implementation of core structures (arrays, linked lists, hash maps, trees, graphs) and algorithms (sorting, searching, recursion, dynamic programming) — evidenced through coursework, competitive programming, or projects
SQL: Experience writing queries (SELECT, JOIN, GROUP BY, subqueries) with at least one RDBMS (PostgreSQL, MySQL, or Oracle), including basic schema design
Git: Collaborative experience including branching, merging, pull requests, and conflict resolution
Cloud Computing: Basic experience with AWS (preferred), Azure, or GCP, including deploying applications
Testing: Unit and integration testing experience (JUnit, Mockito, or equivalent) with TDD principles
SDLC: Full development cycle exposure via internship (3+ months) or capstone project
CI/CD: Experience with at least one tool (Jenkins, GitHub Actions, or equivalent)
Communication: Professional English proficiency (B2+ CEFR)
Previous technical internship(s) of 6+ months in a software engineering role
Experience with microservices architecture and distributed systems design patterns
Familiarity with containerization (Docker) and orchestration (Kubernetes, ECS)
Experience with NoSQL databases (DynamoDB, MongoDB, Redis)
Exposure to AI/ML concepts, GenAI tools, or machine learning frameworks (TensorFlow, PyTorch)
Experience with monitoring and observability tools (CloudWatch, Grafana, Datadog)
Knowledge of cybersecurity fundamentals (OWASP Top 10, secure coding practices, identity management)
Additional language proficiency (German, Luxembourgish) is an advantage
Contributions to open-source projects or published technical work
Experience with agile methodologies (Scrum, Kanban) and tools (Jira, Confluence)
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