Forward Deployed AI Engineer, Energy

• Conduct workshops and expert interviews to understand complex processes and tacit knowledge
• Translate requirements into Agent Blueprints and technical solutions
• Develop AI agents using LLMs, RAG, tool use/function calling, and agent orchestration
• Prepare documents, data, and knowledge for retrieval and agent use
• Build functional prototypes within days and iterate with users
• Create Golden Questions, test sets, and regression tests for evaluation
• Analyze feedback and continuously improve agents
• Clearly communicate technical capabilities and limitations to customers
• Further develop reusable components together with the platform team
• Own use cases from discovery through go-live
• At senior level, advance standards and blueprints for agent building, engage with customer leadership, and scale forward-deployed engineering across the team

• Hands-on experience in GenAI engineering, ideally with at least 1–2 years of experience building LLM applications, RAG systems, prompt engineering, tool use, and agent orchestration
• Excellent production-grade Python skills
• Experience evaluating GenAI applications, such as through test sets, Golden Questions, or regression tests
• Understanding of chunking, retrieval, metadata, and knowledge structures
• Enjoyment of direct customer interaction and the ability to independently structure unclear requirements
• Strong ownership and a pragmatic approach to changing requirements
• Business-fluent German
• Personal projects, GitHub repositories, or other work samples are desirable
• Energy industry expertise, such as market communication, GPKE, EDIFACT, SAP IS-U, or kVASy (nice to have)
• BPMN or comparable process modeling experience (nice to have)
• GCP, Docker, and CI/CD experience (nice to have)
• Knowledge graphs or structured knowledge representation (nice to have)
• Experience in consulting or other customer-facing technical roles (nice to have)

• 30 days of annual leave
• Profit sharing and the opportunity to participate in VSOPs
• Flexible working hours and a remote-first working model
• Offices and smart-office options in and around Hamburg, the Ruhr area/NRW, and Munich
• Direct interaction with subject-matter experts and decision-makers
• Early responsibility and significant scope to shape solutions
• Modern GenAI environment focused on production-grade AI agents
• Supportive team and short decision-making processes