What awaits you
- Drive the development and optimization of (generative) AI applications with a strong focus on model evaluation, retrieval-augmented generation (RAG), and prompt engineering
- Analyze and integrate data from various sources, ensuring high data quality and preparing it for effective AI-driven solutions
- Experiment with LLM models to improve performance and applicability across business use cases
- Collaborate with our AI platform team to enhance and scale AI-driven capabilities
- Work closely with different business units, helping them leverage AI models for real-world applications and continuous improvements
- Share your expertise in GenAI and machine learning with other teams, contributing to knowledge-sharing and innovation within the organization
What Should You Bring Along
- University Degree in Computer Science, Engineering, or a related field
- Strong experience in building AI-driven automation workflows and agents using Python, with a focus on scalable, production-ready solutions
- Proven understanding of agentic systems and orchestration patterns, including multi-agent collaboration, tool integration, and complex workflow design
- Exposure to no-code/low-code automation platforms (e.g., n8n, Make.com, Zapier, Flowise) is a plus, complementing custom-built solutions
- Experience with the usage of LLM APIs (OpenAI, Anthropic)
- Experience with RAG and vector databases (embeddings)
- Knowledge of data ingestion and preprocessing for LLM applications
- Experience with software development best practices (e.g., clean code, unit testing, CI/CD)
- Familiarity with MLOps and best practices for deploying and maintaining AI models in production
- Experience with data pipelines and preprocessing techniques
- Strong problem-solving skills and the ability to work in a collaborative, agile environment
- Excellent English communication skills, both written and spoken