Staff/Senior AI Engineer, AI for Code

At JetBrains, we build developer tools used by millions of engineers. The AI for Code team works on the next generation of coding agents and agentic workflows: systems that can understand codebases, plan and execute multi-step tasks, collaborate with developers, and ship reliable results inside real development environments.

We are looking for a Staff/Senior AI Engineer to join the team and support these efforts. This role is for someone who can take our internal coding models, such as Mellum2, as well as open-weight models, and turn them into production-ready coding agents for our users. You’ll work on model training and fine-tuning, context engineering, tool use, evaluation, feedback loops, and product integration. This is not research in isolation – you’ll build systems that are used by tens of thousands of developers.

• 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.