This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Join a team building next-generation AI solutions and applying them to real business processes. We’re looking for an experienced Software or Data Engineer who wants to grow in the space of Generative AI and LLM-based systems — from a practical, production, and engineering perspective. This role is ideal for someone who understands systems, data, and infrastructure — and is excited to apply those skills to modern AI solutions. You’ll be part of a global team (Europe + US) working on solutions within Crop Science (agriculture innovation). The role is based in Europe, with standard working hours aligned to the local time zone. You will design and build solutions that: leverage LLMs and agent-based systems to automate complex workflows; support the software development lifecycle (SDLC) using AI; enable conversational access to data and insights; integrate AI capabilities into existing engineering and data ecosystems.
Job Responsibility:
Design and develop LLM-powered and multi-agent solutions
Build workflows where AI supports tasks such as requirements analysis, task creation, and code generation
Integrate AI solutions with engineering tools (e.g. code repositories, CI/CD pipelines)
Develop scalable, reliable system components
Build natural language interfaces for querying complex data
Combine structured and unstructured data sources
Ensure accuracy, explainability, and control in AI-driven outputs
Requirements:
Strong Python skills and experience building production systems
Experience with data pipelines
Experience with relational and/or NoSQL databases
Experience with APIs and system integrations
Hands-on experience with CI/CD and version control (e.g. GitHub)
Hands-on experience with cloud platforms (AWS, Azure, or GCP)
Understanding of production systems (monitoring, debugging, reliability)
Interest in Generative AI and LLMs
Initial hands-on experience (projects, experiments, or courses)
Basic understanding of prompt engineering
Basic understanding of RAG / semantic search
Basic understanding of LLM capabilities and limitations
Self-starters who can work independently and take ownership
Engineers who learn quickly and adapt to new technologies
People who value iteration and delivery over perfection
Candidates comfortable working across engineering, data, and business domains
Nice to have:
Background in data engineering or data platforms
Experience with tools like Airflow, dbt, Spark, Snowflake, etc.
Exposure to AI/ML or LLM-based applications
Experience in large organizations or regulated environments
What we offer:
Hands-on experience building production-grade AI/LLM systems
Opportunity to work on real business use cases (not just prototypes)
Collaboration with international teams
Influence on how AI solutions are designed and scaled within the organization
Space to experiment and grow in a rapidly evolving field