Staff/Senior AI Engineer, AI for Code
New
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JetBrainsAI/ML
Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; London, United Kingdom; Madrid, Spain; Munich, Germany; Warsaw, Poland; Yerevan, ArmeniaFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- Machine LearningSoftware EngineeringPrompt EngineeringLLM
Requirements
- Strong software engineering fundamentals and a track record of shipping complex systems to production.
- Hands-on experience building LLM-powered products, coding agents, or other AI systems.
- Experience improving model behavior through systematic iteration, whether via prompting, context engineering, fine-tuning, preference optimization, or broader post-training methods.
- Practical experience with evaluation and benchmarking for LLM systems, including defining task-grounded success metrics and catching regressions.
- Experience working from noisy real-world signals rather than only from clean benchmark datasets.
- Good judgment about trade-offs between model quality, latency, reliability, privacy, and cost.
- Confidence working with ambiguity and taking ownership of a direction over multiple iterations.
- Strong communication skills and the ability to align engineering and product decisions.
Responsibilities
- 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.
- 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 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 in ambiguous areas.
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