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Amsterdam
12 Jun 2026
Senior Research Engineer (Agentic Behavior) logo

Senior Research Engineer (Agentic Behavior)

JetBrains

Amsterdam
12 Jun 2026
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Senior Research Engineer (Agentic Behavior)

JetBrains seeks a Senior Research Engineer to build evaluation infrastructure and improve AI coding agents for Kotlin. The role involves error analysis, benchmark creation, and post-training techniques. Requires strong Python and LLM eval experience.

AIHybridFull-timeSeniorPythonSQL

Senior Research Engineer (Agentic Behavior)

JetBrains seeks a Senior Research Engineer to build evaluation infrastructure and improve AI coding agents for Kotlin. The role involves error analysis, benchmark creation, and post-training techniques. Requires strong Python and LLM eval experience.

Apply
AIHybridFull-timeSeniorPython

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site with remote flexibility

Employment Type

Full-time

Experience Level

Senior

Core Qualifications

Technical (Must-have)
PythonSQLKotlinLLMsAI coding agentsData analysisEvaluation pipelinesPost-trainingSFTDPOGRPOPyTorchAWS AthenaGitCI/CD
Soft Skills
Problem solvingProduct-aware mindsetOwnershipCollaboration

Preferred Qualifications

Technical (Nice-to-have)
RLHFTRLverlMegatronInspect AIPromptfooLM-evaluation-harnessWeights & BiasesMLflowLangfuseAndroidGradleKMPSpringKtor

Key Responsibilities

  • •Design and implement tooling to capture, classify, and analyze errors from AI coding agents generating Kotlin code.
  • •Build observability pipelines over agentic traces from JetBrains IDEs, Junie, Claude Code, Cursor, etc.
  • •Design, implement, and maintain evaluation pipelines for Kotlin code generation quality.
  • •Build simulation environments for realistic Kotlin developer tasks.
  • •Own evaluation infrastructure: metrics, experiment tracking, regression checks, benchmarking.
  • •Experiment with post-training techniques (SFT, DPO, GRPO) to improve Kotlin-specific model behavior.
  • •Investigate context engineering approaches (CLAUDE.md, compiler-as-verifier, Kotlin LSP, MCP).
  • •Run A/B comparisons and before/after analyses on real codebases.
  • •Collaborate with model providers (Anthropic, OpenAI, Google) to drive improvements.
  • •Design and build open-source benchmarks for AI coding agent performance on Kotlin tasks.
  • •Create task datasets covering server-side, multiplatform, build systems, Android, etc.
  • •Maintain and evolve benchmarks to remain challenging and contamination-resistant.
Research EngineerKotlinAI agentsLLMsEvaluation infrastructurePost-trainingBenchmarksJetBrainsAmsterdam
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