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.
Tasks
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
Requirements
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
Benefits
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
We are looking forward to hear from you!