Senior GenAI & LLM Engineer / Architect / Expert

2w2 weeks ago

Bertrandt

Regensburg, DE · Full-time · €80,000 – €110,000

About this role

Gestalte die Zukunft der KI with us! As part of our team, you develop innovative solutions based on Large Language Models and Multi-Agent Systems. Together we build scalable AI infrastructures and integrate modernste Technologien into complex system landscapes.

Conception and architecture of AI systems on basis of Large Language Models like ChatGPT and Claude. Development and optimization of Multi-Agent Systems such as RooCode and LangGraph. Aufbau skalierbarer AI- and MLOps-Infrastrukturen with CI/CD for ML, Model Registry, Monitoring, and Observability.

Erstellung of Prompt-Pipelines, Retrieval-Augmented-Generation concepts (RAG), and complex workflow automations. Integration of KI-Komponenten into existing system landscapes using Microservices, APIs, and cloud-native architectures. Zusammenarbeit with product teams and stakeholders on innovative KI-Features.

Join a team with flache Hierarchien and teamorientierte Arbeitsweise. Benefit from Buddy-Programm, internes Gesundheitsmanagement, and betriebliche Altersvorsorge. High Lernbereitschaft meets cutting-edge KI-Technologien in projects including Verteidigungsindustrie.

Requirements

Very good German skills (C1–C2 level) required
Completed degree in Computer Science, Data Science, Mathematics or comparable field
Experience with LLM-Models, Prompt Engineering and RAG
Solid knowledge in Python, AI-Frameworks (LangChain, LangGraph, FastAPI)
Experience building Multi-Agent-Workflows or agent-based AI systems
Knowledge of Cloud environments (Azure, AWS or GCP), containers (Docker, Kubernetes)
Understanding of Software-Architecture patterns (Microservices, Event-Driven Architecture, REST/GraphQL)
Openness for projects in the Verteidigungsindustrie

Responsibilities

Conception and architecture of AI systems based on Large Language Models (e.g., ChatGPT, Claude)
Development and optimization of Multi-Agent Systems (e.g., RooCode, LangGraph)
Build scalable AI- and MLOps-Infrastrukturen (CI/CD for ML, Model Registry, Monitoring, Observability)
Creation of Prompt-Pipelines, Retrieval-Augmented-Generation-Konzepten (RAG), complex workflow automations
Integration of KI-Komponenten into existing system landscapes (Microservices, APIs, cloud-native architectures)
Collaboration with product teams and stakeholders on development of innovative KI-Features