招聘

Research Engineer (Agentic Behavior – Kotlin AI Value Stream)
Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; Madrid, Spain; Munich, Germany; Prague, Czech Republic; Warsaw, Poland; Yerevan, Armenia
·
On-site
·
Full-time
·
2w ago
At Jet Brains, 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 Jet Brains IDEs, Junie, Claude Code, Cursor, and other coding agents.
Build evaluation pipelines
-
Design, implement, and maintain evaluation pipelines that measure Kotlin code generation quality across dimensions, including correctness, idiomaticity, build success, framework usage, and test coverage.
-
Build simulation environments where coding agents can be measured on realistic Kotlin developer tasks – from greenfield KMP projects and Gradle dependency management to migrating Spring applications from Java to Kotlin.
-
Own evaluation infrastructure: metrics, experiment tracking, automated regression checks, and reproducible benchmarking.
Research methods for improving agent and model behavior on Kotlin
-
Experiment with post-training techniques (SFT, DPO, GRPO) to improve how models handle Kotlin-specific patterns, idioms, and frameworks.
-
Investigate context engineering approaches: CLAUDE.md/AGENTS.md files, compiler-as-verifier feedback loops, Kotlin LSP integration, and MCP-based tooling.
-
Run experiments to measure impact: A/B comparisons, benchmark suites, and before/after analyses on real codebases.
-
Collaborate with model providers (Anthropic, OpenAI, and Google) to translate Kotlin-specific findings into model improvements.
Build public Kotlin benchmarks
-
Design and build open-source benchmarks that measure AI coding agent performance on Kotlin tasks and eventually become the standard reference for the ecosystem.
-
Create task datasets covering the breadth of Kotlin usage: the server side (Spring, Ktor), multiplatform projects (KMP), build systems (Gradle), Android, library development, and others.
-
Include both mined real-world tasks and carefully designed synthetic tasks that test specific Kotlin capabilities.
-
Maintain and evolve benchmarks as models improve, ensuring they remain challenging, relevant, and contamination-resistant.
We'll be happy to have you on board if you have:
-
Hands-on experience building evaluation or analysis pipelines for LLMs or AI coding agents in a research or production setting.
-
Strong Python engineering skills (at least three years), with the ability to write clean, maintainable code in data-heavy and ML-adjacent codebases.
-
Experience with data analysis at scale: querying large datasets (SQL/Athena), building data pipelines, and performing statistical analysis of experimental results.
-
The ability to own projects end to end – from identifying a problem in agent traces to designing an eval, running experiments, and shipping a fix.
-
A product-aware mindset: You care about how agents are actually used by developers and can translate real failure modes into evaluation and training work.
-
Familiarity with Kotlin or a strong willingness to develop deep Kotlin expertise (you'll be living in Kotlin codebases daily).
Our ideal candidate would also have experience with:
-
Post-training LLMs: SFT, RLHF, DPO, GRPO – either hands-on training or designing the data and reward pipelines that feed into training.
-
Modern deep learning frameworks (Py Torch) and LLM training stacks (TRL, verl, Megatron, or similar).
-
AI agent development: tool-using agents, multi-step coding workflows, agentic frameworks.
-
Evaluation frameworks and tools: Inspect AI, Promptfoo, LM-evaluation-harness, or custom eval pipelines.
-
Experiment tracking and observability: Weights & Biases, MLflow, Langfuse, or similar.
-
The Kotlin ecosystem: Android, Gradle, KMP, Spring, Ktor – with an understanding of the developer workflows that agents need to support.
-
Contributing to or maintaining open-source projects, especially benchmarks or evaluation tools.
Don't check every box? That's okay – if you're excited about this work and bring strong fundamentals, we'd love to hear from you. We're happy to talk and provide the training you need to grow into the role.
Why join Jet Brains?
-
Strong base salary. We offer competitive pay that reflects your skills and experience.
-
Flexible work location. Enjoy the freedom to work from home or from the office.
-
Remote work. Spend up to 30 days per year working remotely from abroad.
-
Extra time off. More days to relax, recharge, and do the things you love.
-
Medical insurance allowance. Enjoy peace of mind for you and your family
-
Learning and development opportunities. Access to conferences, courses, and language classes.
-
Relocation support. We help make your move as smooth and stress-free as possible.
-
Language classes. Pick up the local language or sharpen your English skills.
-
Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
-
Mental health support. To help you feel your best, we provide easy access to professional mental health services.
-
Sports benefit. Enjoy an on-site gym or sports club stipend.
-
Internal events. Join company-wide celebrations and team gatherings.
Some benefits may vary depending on location.
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
总浏览量
0
申请点击数
0
模拟申请者数
0
收藏
0
相似职位

Machine Learning Scientist
Adyen · Amsterdam

Machine Learning / Computer Vision Engineer for XR Labs - Amsterdam
Qualcomm · Amsterdam, North Holland, Netherlands

AI - Forward Deployed Engineer
Wipro · Amsterdam, Netherlands

SAP Business AI Architect - Netherlands
Infosys · Amsterdam, Netherlands

AI Deployment Strategist - Netherlands
Mistral AI · Amsterdam
关于JetBrains

JetBrains
BootstrappedJetBrains develops integrated development environments (IDEs) and software development tools for programming languages including Java, Kotlin, Python, JavaScript, and others. The company is known for products like IntelliJ IDEA, PyCharm, WebStorm, and the Kotlin programming language.
1,001-5,000
员工数
Prague
总部位置
薪资范围
2个数据点
Mid/L4
Mid/L4 · Market Analyst
2份报告
$169,300
年薪总额
基本工资
$130,000
股票
-
奖金
-
$116,300
$169,300
新闻动态
JetBrains says ROI-proof pressure in cloud shifts will repeat for AI agents - 디지털투데이
디지털투데이
News
·
2d ago
JetBrains announces Pycharm 2018.2 - Packt
Packt
News
·
2d ago
JetBrains Central vs Intent (2026): Control Plane or Dev Workspace - Augment Code
Augment Code
News
·
1w ago
My Full Rust Interview With JetBrains Is Now On YouTube! Https://www.youtube.com/watch?v=nOSxuaDgl3s [ea0b42] - Fathom Journal
Fathom Journal
News
·
1w ago