Intelligence architecture, own the technical architecture of our reasoning, inference, and orchestration layers
Knowledge systems, manage, extend, and refactor knowledge bases, and intelligence primitives across crops and use cases
Reasoning capabilities, improve reasoning across structured data, time-series, events, and insights using LLMs and statistical models
Testing and validation, design automated testing pipelines and validate outputs against historical data, synthetic scenarios, and real customer datasets
Tool integrations, integrate with external tools, data sources, APIs, and AI services with clean technical interfaces
Releases, plan, implement, test, and ship intelligence releases on a regular cadence

Strong background in software engineering, AI engineering, or applied machine learning
Proven experience building, testing, and maintaining complex AI or intelligence systems
Excellent programming skills in Python and experience with data-intensive and time-series systems
Experience with modern AI stacks including LLMs, embeddings, and orchestration frameworks
Strong system design skills with a focus on maintainability, testability, and scalability
Ability to work autonomously with clear ownership in a fast-moving environment
Strong communication skills and experience working cross-functionally
Willingness to travel and work directly with customers
Experience with knowledge graphs, semantic models, or reasoning systems (Nice to Have)
Experience designing testing and validation pipelines for AI systems (Nice to Have)
Familiarity with cloud-native architectures and production AI deployments (Nice to Have)
Exposure to agricultural, industrial, or sensor-driven data domains (Nice to Have)

AI Engineer – Bucharest, Munich

Key skills