Overview
We're an AI Engineering team focused on applied AI - we focus on integrating AI features into business and products. We handle the full agent development lifecycle: design, implementation, tool development, testing, and evaluation. Since ready-made datasets and metrics don't always exist for our use cases, we often create those as well.
We develop agents using the Koog framework (built right here at JetBrains) and work closely with the Koog team, providing feedback and occasionally contributing general features back to the framework when they're broadly useful beyond our specific agents.
Currently, we're preparing our SWE agent for open source release, including writing blog articles about the development process and lessons learned.
What You'll Do
Join our team working on cutting-edge AI agent development. Depending on when you start and the project needs, you might work on:
Implementing new agent capabilities and tools
Designing and running agent evaluation experiments
Contributing to the Koog framework features
Sharing your work in blog articles - a chance to build your CV and online presence by showcasing what you’ve done
You'll get hands-on experience with both the research side (studying problems, running experiments) and engineering side (implementing solutions, writing robust code). This is a 6-month internship where you'll gain deep experience in both AI agent development and production-quality software engineering.
Strong software engineering fundamentals - you know your OOP, design patterns, and why SOLID principles matter
Proficiency in at least one JVM language (we'd love Kotlin, but Java works great too)
Demonstrated interest in AI agents - whether through personal projects, coursework, research, or just building cool stuff on weekends
Understanding of LLM fundamentals - how transformers work, what tokenization does, plus modern capabilities like tool calling, structured outputs, and multimodal processing
Basic ML/statistics knowledge - comfortable with datasets, evaluation metrics, and core statistical concepts