Introduction

You design agent-based AI systems that make a real difference from the idea stage to actual implementation.

Tasks

• You design agent architectures, model harnesses, prompt strategies, and context management for agent-based AI systems.
• You implement retrieval-augmented generation, vector search, and multi-stage orchestration with tool calling and MCP integrations.
• You evaluate generative behavior, security, and failure modes such as hallucinations, and establish monitoring and countermeasures.
• You build reproducible evaluation pipelines and conduct metric-driven experiments.
• You transition solutions into production using MLOps and software engineering practices while remaining closely aligned with users and stakeholders.
• You stay up to date with the state of the art in foundation models and agentic AI and evaluate their potential for use on the platform.

Placeholder Job Ad Video (do not remove)

Qualifications

• You have several years of professional experience in the field of machine learning, including practical work with foundation models such as agents or RAG in production applications.
• You have experience bringing model-based features from prototype to production together with MLOps and software engineering.
• You have solid Python skills as well as experience with model APIs and LLM tooling such as Hugging Face, LiteLLM, LangChain, or comparable tools.
• You are familiar with RAG, vector stores, prompt design, as well as agent and workflow orchestration, and have knowledge of evaluation methods for generative systems, including automated tests, metrics, and tracing, as well as knowledge of privacy, safety, and responsible AI assessment.
• You excel in teamwork, communication, solution orientation, and presentation skills.
• Very good German and very good English skills, both written and spoken, round off your profile.

Contact and further information