Research Engineer (Agentic Behavior – Kotlin AI Value Stream)
JetBrains · Amsterdam, Netherlands | Belgrade, Serbia | Berlin, Germany | Limassol | Madrid, Spain | Munich, Germany | Prague, Czech Republic | Warsaw, Poland | Yerevan · Kotlin Ecosystem
About this role
JetBrains is hiring a mid-level Research Scientist in the machine learning function based in Amsterdam, Netherlands | Belgrade, Serbia | Berlin, Germany | Limassol | Madrid, Spain | Munich, Germany | Prague, Czech Republic | Warsaw, Poland | Yerevan. The posting calls out experience with Python, Java, Kotlin, SQL.
- Role
- Research Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Amsterdam, Netherlands | Belgrade, Serbia | Berlin, Germany | Limassol | Madrid, Spain | Munich, Germany | Prague, Czech Republic | Warsaw, Poland | Yerevan
- Department
- Kotlin Ecosystem
More roles at JetBrains
Job description
from JetBrains careersAt JetBrains, code is our passion. Ever since we started, back in 2000, we've been striving to make the strongest, most effective developer tools on earth. Today, AI-powered coding agents are becoming a core part of how developers write Kotlin – and we want to make sure they write it well.
The Kotlin AI Value Stream team is responsible for how AI agents understand, generate, and improve Kotlin code across all platforms: Android, Kotlin Multiplatform, server-side, web, desktop, and others. We build the evaluation infrastructure, error analysis tools, and post-training pipelines that measure and improve agent behavior on real Kotlin developer tasks.
As a Research Engineer on this team, you'll own the end-to-end loop: Analyze how agents fail on Kotlin → build evals that capture those failures → research and implement methods to fix them → measure the improvement. Your work will directly shape how millions of developers experience Kotlin through AI coding agents.
As part of our team, you will:
Build tools for agentic error analysis
- Design and implement tooling to systematically capture, classify, and analyse errors that AI coding agents make when generating Kotlin code.
- Build observability pipelines over agentic traces – mining patterns from agent sessions in JetBrains IDEs, Junie, Claude Code, Cursor, and other coding agents.