Build production-ready coding agents and agentic workflows for real developer tasks inside JetBrains products
Turn promising model capabilities into dependable product behavior through prompt design, context construction, fine-tuning, instruction-tuning, or other post-training techniques where appropriate
Design and improve the agent loop itself, including tool use, execution strategy, safeguards, and task completion quality
Create evaluation suites and quality infrastructure for agent behavior, including online and offline evaluations, regression checks, failure analysis, and release criteria
Build feedback loops from real usage, using logs, user signals, and edge cases to improve data, evaluations, and agent behavior
Work with both hosted frontier APIs and self-hosted or open-weight models, making pragmatic decisions about where each model belongs based on capability, latency, reliability, privacy, and cost
Collaborate closely with product managers, software engineers, ML engineers, and researchers to ship features end to end
Help define the technical direction for future work, especially in ambiguous areas where we need strong judgment rather than a prewritten playbook