Software Engineer (RAG, Knowledge Graph & Agent Systems)

Quick Facts

• Role: Software Engineer focused on RAG, Knowledge Graph, and Agent Systems

• Work style: Hybrid

• Employment: Permanent full-time

• Locations: Berlin, Baden-Baden, or Verl

Description

Build and optimize AI-powered, scalable product functions using RAG pipelines, knowledge graphs, and agentic multi-step workflows. Develop and integrate retrieval and context strategies (retrievers, embeddings, indexing, chunking, prompting) and evaluate performance and cost. Collaborate with platform engineers and product/domain teams to deliver user-ready AI capabilities.

Responsibilities

• Develop and optimize RAG pipelines (retriever components, embeddings, indexing, evaluation logic)

• Integrate knowledge graphs to provide structured context for AI systems and agents

• Implement agentic multi-step workflows using MCP clients, orchestration logic, and supporting tools

• Design prompting strategies, chunking concepts, and context preparation methods aligned to product requirements

• Integrate AI models into existing platforms and systems

• Optimize performance and cost; run benchmarks for RAG and agent architectures

• Work with Platform Engineers on shared SDKs, gateway patterns, and architecture standards

• Create and maintain technical documentation and contribute to context engineering best practices

• Partner with product and domain teams to build AI-supported features for users

• Build and further develop the AI platform to sustainably increase software development productivity

• Conceive and implement LLM-based, agentic, knowledge-graph solutions for automation and smarter developer workflows

Benefits

• Modern technology and data-driven insights to build reliable, scalable AI product capabilities

• Hybrid working environment and interdisciplinary collaboration

• Opportunity to shape a long-term AI platform that improves developer productivity