Germany
Universal Quantum
Adesso SE
Senior GenAI Engineer (all genders)
Germany
Bremen, Bremen, Germany · Frankfurt, Hesse, Germany · Hanover, Lower Saxony, Germany · Rostock, Mecklenburg-Vorpommern, Germany · Stralsund, Mecklenburg-Vorpommern, Germany · Aachen, North Rhine-Westphalia, Germany · Bonn, North Rhine-Westphalia, Germany · Cologne, North Rhine-Westphalia, Germany · Dortmund, North Rhine-Westphalia, Germany · Dusseldorf, North Rhine-Westphalia, Germany · Essen, North Rhine-Westphalia, Germany · Münster, North Rhine-Westphalia, Germany · Paderborn, North Rhine-Westphalia, Germany · Siegen, North Rhine-Westphalia, Germany · Koblenz, Rhineland-Palatinate, Germany · Dresden, Saxony, Germany · Leipzig, Saxony, Germany · Jena, Thuringia, Germany · Berlin, Germany · Hamburg, Germany
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YOUR ROLE
- Develop RAG systems: You conceptualize and implement scalable Retrieval-Augmented Generation architectures for business-critical enterprise applications.
- Implement LLM workflows: You develop structured LLM-based workflows including tool integration, context control, and error handling.
- Implement MCP integration: You develop MCP-compliant tool interfaces and structured function calls within LLM and agent systems.
- Establish evaluation logics: You define test sets, evaluation metrics, and comparison methods for systematic quality measurement of LLM and RAG systems.
- Optimize performance and cost-effectiveness: You analyze token consumption, latency behavior, and model selection, and optimize systems regarding stability and costs.
YOUR PROFILE
- Education & Experience: You have a completed degree in Computer Science, Data Science, Computational Linguistics, or a comparable technical field, and at least 3 years of experience in the development and production deployment of GenAI or LLM-based applications in an enterprise context.
- Expertise in GenAI Systems: You have a deep understanding of transformer architectures, embedding models, retrieval strategies, tool calling, and structured output mechanisms.
- Apply Tech Stack: You work confidently with frameworks like LangChain or LlamaIndex, vector databases, cloud-based LLM-APIs, and API integrations.
- Quality-Oriented Approach: You work iteratively, are measurement-driven, and have a clear focus on robustness, response quality, and controllability.
- Language Skills: You communicate fluently and professionally, both verbally and in writing, in German and English.
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