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

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

We are looking forward to hear from you!