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# GenAI Engineer - Data Scientist

- **Company:** Siemens Energy
- **Location:** Munich, ND, United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Debugging, Python (Programming Language), Machine Learning, Unstructured Data, Multi-Agent Systems, Prompt Engineering, Generative AI, Information Technology, Automation Anywhere
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/obkii028xn

## About the Role

* Academic background in computer science, machine learning or related fields.
 * Proven experience in agentic workflow frameworks, unstructured data processing, and RAG architectures.
 * Hands-on Python skills and ability to debug and optimise complex AI systems. Strong understanding of prompt engineering, few-shot learning, and techniques to improve model outputs.
 * Excellent problem-solving, analytical, communication skills, and an agile mindset for managing multiple projects.
 * Fluent English is required while German language skills are a plus.
 * Willingness to travel (~25%) mainly in Central Europe.

## Description

* Design and implement document processing pipelines to structure complex technical documentation for efficient retrieval.
 * Develop and optimise Retrieval-Augmented Generation (RAG) systems for accurate information synthesis from large-scale repositories.
 * Architect and deploy multi-agent AI workflows using frameworks such as LangGraph, CrewAI, or AutoGen.
 * Create evaluation frameworks to assess and enhance the accuracy of multi-agent AI systems.
 * Implement guardrails and validation mechanisms to ensure outputs meet engineering standards and governance requirements.
 * Drive continuous improvement through prompt engineering, fine-tuning, and experimentation with agent orchestration patterns., You'll join a passionate, multi-disciplinary team dedicated to driving innovation in AI and digital transformation across Siemens Energy. The team works closely with domain engineers, data scientists, and external partners to develop solutions that enhance operational efficiency and support our commitment to sustainability. Collaboration and knowledge-sharing are at the heart of our approach, ensuring that every project benefits from diverse expertise and perspectives.


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