- Develop AI applications using state-of-the-art (Gen)AI technology.
- Translate business requests into AI applications.
- Pilot prototypes in production processes to demonstrate their value.
- Deploy prototypes to production to obtain reliable, scalable systems.
- Present your results in a clear manner and discuss them with multi-functional project teams.
- Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), and with other AI engineers in the team (e.g. for knowledge sharing).
Technical and Qualified Requirements
Technical skills
- Strong expertise in Python
- Strong knowledge of state-of-the-art AI and statistical methods
- Proven proficiency with deploying scalable AI applications to production
- Experience using LLMs and commonly used libraries to interact with LLMs (Langchain, Llamaindex, ...)
- Hands-on experience with Azure Cloud, and Azure Data AI services
- Strong Expertise with version control (Git, GitHub)
- Expertise with CI/CD pipelines, and modern software development best practices
- Experience with Agentic AI frameworks (Langgraph, AutoGen, CrewAI, ) is a big plus
- Experience with MLOps tools and frameworks (e.g. MLflow, Kubeflow, TFX) is a big plus