You drive the development and optimization of (generative) AI applications with a strong focus on model evaluation, retrieval-augmented generation (RAG), and prompt engineering.
You analyze and integrate data from various sources, ensuring high data quality and preparing it for effective AI-driven solutions.
You experiment with LLM models to improve performance and applicability across business use cases.
You collaborate with our AI platform team to enhance and scale AI-driven capabilities.
You work closely with different business units, helping them leverage AI models for real-world applications and continuous improvements.
You 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 as a GenAI DevOps Engineer
A university degree in Computer Science, Engineering, or a related field
At least 5-7 years of experience as a Python Developer
Experience with the usage of LLM APIs (OpenAI, Anthropic)
Experience with prompt engineering
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
