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As an AI Engineer (w/m/d), you take ownership of the architecture and operation of our AI agents. You work closely with Data Scientists to turn AI prototypes into robust, reliable, and scalable production systems – and continuously evolve them.
Job Responsibility:
Take ownership of the architecture and operation of our AI agents.
Work closely with Data Scientists to turn AI prototypes into robust, reliable, and scalable production systems – and continuously evolve them.
Design, Build & Run: Architect reliable AI systems.
Measure & Improve Quality: Define metrics, run systematic evaluations, and conduct A/B testing.
Bridge the Gap: Work closely with Data Scientists to bring prototypes into production.
Explore New Frontiers: Evaluate and apply the latest AI/ML technologies and practices.
Requirements:
Apply software engineering best practices consistently – testing, clean code, and solid architecture.
Stay curious and actively explore new technologies, applying them where they create real value.
Work effectively in agile, cross-functional teams where fast delivery, learning, and iteration are the norm.
Use Python and AI frameworks such as Pydantic-AI, LangGraph, or similar to build robust solutions.
Use Docker and docker-compose to containerize applications.
Work confidently with Git as a core tool for team collaboration.
Nice to have:
Bring experience with SQL, Spark, Kubernetes, Grafana, Prometheus, Graylog, Jenkins, or Java, and apply it to further improve our systems.