Job Summary: The Prompt End Engineer will be part of the AI & Innovation team and will play a critical role in shaping the development and deployment of prompt-based interactions using large language models (LLMs). This is a full-time, hybrid role (remote and/or in-office in Frankfurt/Eschborn), ideal for someone who thrives in cross-functional environments and enjoys building real, production-grade AI capabilities.
We are looking for a motivated and technically skilled team member who is excited about prompt engineering, automation, and AI implementation at scale. This position offers a unique opportunity to directly influence how users interact with advanced language models and to contribute to cutting-edge product development across multiple domains.
Duties/Responsibilities:
- Design, implement, and maintain stable, scalable prompts for production use across chatbots, virtual agents, and RAG (Retrieval-Augmented Generation) systems
- Collaborate with engineering, DevOps, and product teams to embed prompt strategies into live applications and backend pipelines
- Automate prompt testing, monitoring, and deployment workflows using Python and tools such as LangChain or similar frameworks
- Analyze and refine prompt outputs to improve performance, reliability, and reduce hallucinations or irrelevant responses
- Support the development of internal prompt management systems and prompt libraries
- Stay up to date with LLM developments and help translate innovations into usable, scalable product components
Preferred Skills/Abilities:
- Degree in Computer Science, Artificial Intelligence, Computational Linguistics, or a related field
- Hands-on experience working with large language models (e.g. OpenAI, Anthropic, HuggingFace)
- Proficiency in Python, including using it for scripting, automation, or API integrations
- Strong understanding of prompt design, token/context management, and few-/zero-shot prompting methods
- Excellent communication skills in both English and German
- Ability to work in an agile team environment and contribute across functions
- Familiarity with RAG, vector search, embeddings, or prompt evaluation techniques
- Experience with CI/CD pipelines for prompt systems or automated prompt testing
- Knowledge of tools like Git, Notion, Slack, or internal LLM sandboxes
- Must be fluent in: English and german
Work Environment:
This is a hybrid role with flexibility for remote work, with regular collaboration with teammates located in Frankfurt/Eschborn.
What We Offer:
- A flexible hybrid work model
- A collaborative, low-ego team culture
- Modern tools and infrastructure for AI product development
- Dedicated time and budget for learning and exploration
- Flat hierarchies and short decision-making paths