EU remote
Extracurricular Internship: AI-Assisted Software Engineering Intern (f/m/div.)
About this role
Your contribution to something big: Join us in shaping the future of software engineering through Generative AI. As an AI-Assisted Software Engineering Intern, you will contribute to the development of innovative AI-powered solutions that support software engineers throughout the Software Development Life Cycle (SDLC). Working alongside experienced engineers, you will research, prototype, and evaluate technologies that help improve development efficiency, software quality, and developer experience.
In this role, you will: Research emerging AI-assisted software engineering workflows and identify opportunities to apply Generative AI across the SDLC. Design and develop automated solutions using LLM APIs, prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and context-window optimization techniques. Support the integration of AI-powered tools into software development workflows, CI/CD pipelines, and cloud environments.
Define and implement metrics to evaluate the impact of AI solutions on productivity, software quality, usability, and adoption. Collaborate with software engineers to gather feedback, validate concepts, and continuously improve developed solutions. Contribute through code reviews, technical documentation, demonstrations, and knowledge-sharing activities. Explore and evaluate emerging AI technologies and translate them into practical developer tools.
What distinguishes you? Education: Final-year Bachelor's or Master's student, or recent graduate (less than one year), in Software Engineering, Computer Engineering, Computer Science, Artificial Intelligence, or a related field. Experience: Initial academic, personal, or internship experience in software development or AI-related projects. Exposure to Generative AI technologies and modern software development practices is advantageous.
Know-how: Knowledge of Python programming; experience with C or C++ is a plus. Familiarity with some of the following areas: LLM APIs, prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, CI/CD pipelines, cloud platforms, or AI-assisted development tools. Understanding of software development processes and developer workflows. Languages: Good communication skills in English, both written and spoken. Working Style and Methods: Structured and analytical approach to problem-solving.