At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
The Python Ecosystem team builds PyCharm – one of the most popular Python IDEs in the world – along with the Python plugin for IntelliJ IDEA. As AI changes how developers write, debug, and ship code, we’re making our Python tools AI-native. We’re looking for an AI Lead to drive this effort by shaping the architecture, building key components hands-on, and guiding the team in making strong decisions around AI-powered product development.
In this role, you will:
Lead the technical design of AI features in PyCharm and our Python tooling, including MCP integrations, agent workflows, tool design, and context management.
Prototype and ship features yourself – this is a hands-on technical leadership role.
Help the team adopt AI technologies effectively by providing technical guidance, reviewing approaches, and sharing practical patterns.
Evaluate emerging AI tools, frameworks, and providers, and make pragmatic decisions about what to build and what to integrate.
Work closely with product managers, ML engineers, QA specialists, and senior developers to turn product ideas into solid technical plans.
Navigate a large Kotlin/Java codebase and expose IntelliJ Platform capabilities – such as code analysis, inspections, refactorings, and type inference – to AI-powered workflows.
Contribute to cross-team AI efforts and help define shared engineering patterns where appropriate.
We’d love to talk to you if you have:
Strong software engineering experience, particularly in Python and/or Kotlin/JVM.
Deep, hands-on familiarity with modern AI tooling for developers, including coding assistants, agents, MCP, and LLM-based workflows.
Experience working in large, mature codebases and delivering meaningful technical change without compromising quality.
Familiarity with LLM evaluation and benchmarking.
A track record of making good technical decisions in fast-moving, ambiguous areas like proposing architectures, building prototypes, and iterating based on feedback.
Strong communication skills and the ability to influence technical direction without formal authority.
A strong product sense and care about solving real user problems, not just building interesting technology.