As an AI Engineer, you take ownership of the architecture and operation of AI agents.
Collaborate closely with Data Scientists to turn AI prototypes into robust production systems.
Define metrics, run systematic evaluations, and conduct A/B testing to measure and improve quality.
Evaluate and apply the latest AI/ML technologies and practices in production.

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.
Bonus (nice to have): Bring experience with SQL, Spark, Kubernetes, Grafana, Prometheus, Graylog, Jenkins, or Java, and apply it to further improve our systems.

AI Engineer

Key skills