AI Engineer (m/w/d)

Worldwide | Sept. 3, 2026

Report as Closed

Company: adorsys GmbH

Country: Worldwide

Type: Onsite

Employment: Experienced

Description:
What awaits you

• Development and operation of production-ready multi-agent systems and autonomous workflows
• Conception of RAG architectures with knowledge graphs and hybrid retrieval strategies
• Building document processing pipelines for information extraction from complex documents
• Fine-tuning and optimization of LLMs and multimodal models
• Design of agent stacks with modern standards such as MCP and prompt engineering
• Pipelines for preprocessing, entity resolution and data harmonization (data engineering)
• Integration of LLM applications into existing systems
• Evaluation, monitoring and performance optimization of productive AI systems
• Close collaboration in cross-functional teams

• Several years of experience with production-ready GenAI and multi-agent systems
• In-depth knowledge of agent engineering and frameworks (e.g. LangGraph, AutoGen, CrewAI)
• Very good Python knowledge and experience with LangChain / LangGraph
• Experience with LLM APIs (Claude, OpenAI, Gemini) and fine-tuning (SFT, RLHF)
• Expertise in document processing and the processing of structured / unstructured data
• Experience in data engineering (ETL, preprocessing, data pipelines)
• Understanding of production ML: deployment, monitoring, performance
• Very good knowledge of German (C1), good knowledge of English and strong teamwork skills
• You get bonus points (not a must) for knowledge of knowledge graphs, Semantic Web or Graph ML. Experience with cloud AI platforms and MLOps (e.g. AWS Bedrock, MLflow, Docker, Kubernetes) and industry knowledge in tax, law or finance

You will become part of our Augmented AI Tribe. A team that turns new technologies such as LLMs, RAG, agentic systems, graph-based AI and NLP into reliable products and reusable capabilities. We combine scientific methodology with pragmatic engineering and deal with topics such as Agentic Ecosystem and Neurosymbolic AI to Sovereign and Physical AI.
We work iteratively, hands-on and co-creatively: share ideas early, question assumptions with evidence and pass on knowledge across project boundaries. For us, leadership means enablement through trust and ownership instead of micromanagement. You will have the space to build and further develop current topics independently. You are in close contact with software engineers, knowledge engineers, data engineers, data architects and product teams (m/f/d).

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