Siemens Energy

• Design and implement AI agent workflows with tools such as LangChain, LangGraph, and LLM orchestration.
• Build and maintain RAG pipelines with vector stores like FAISS, Pinecone, and Redis, ensuring flawless data handling.
• Work with structured (SQL) and unstructured data (PDFs) on platforms like e.g. Snowlfake 
• Fine-tune or adapt existing models (LoRA, PEFT) for specific tasks, driving world-class performance.
• Validate and improve system performance using frameworks like RAGAS or custom evaluators.
• Integrate and design solutions compatible with Model Context Protocol (MCP) for standardized multi-agent context handling.
• Contribute to technical documentation, internal knowledge sharing, and optionally publish research papers or blog posts.

• Strong experience in Python and GenAI tooling (LangChain, LangGraph, etc.).
• Master's degree in Computer Science, Engineering, Science or equivalent
• Deep understanding of LLM APIs (OpenAI, Google Gemini, Anthropic Claude, Mistral, etc.).
• Hands-on experience with RAG, semantic search, and vector databases (Redis, FAISS, Pinecone, etc.).
• Familiarity with structured and unstructured data pipelines.
• Experience with evaluation/validation tools like RAGAS, LangSmith, or custom QA pipelines.
• Interest in model fine-tuning techniques (LoRA, QLoRA, timely tuning).
• Working knowledge or willingness to learn Model Context Protocol (MCP).

At Siemens Energy, we are more than just an energy technology company. With ~100.000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.

Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.      

• In addition to an attractive remuneration package in line with the market, you can expect an attractive employer-financed company pension scheme
• We also offer the opportunity to become a Siemens Energy shareholder
• We offer our employees the opportunity to work flexibly and remotely, and our inspiring offices provide space for collaboration and creativity
• The professional and personal development of our employees is very important to us. We provide them with the opportunities to learn and develop in a self-determined way, various attractive programmes and learning materials are available for this purpose
• In relation to the "compatibility of family and work", we have a wide range of offers, e.g. flexible working time models, childcare places at many locations, the possibility of trial part-time work or even a sabbatical