AI Engineer

Descrizione del posto

Join our innovative team for exciting GenAI projects! Enjoy a dynamic work environment with great opportunities. Tasks Develop and implement LLM-based applications and solutions. Conduct workshops, proofs-of-concept, and collaborative projects. Evaluate solutions using Evaluation Driven Development principles. Skills Bachelor's degree in Computer Science or related field required. Expertise in Retrieval-Augmented Generation systems essential. Strong Python skills and software engineering best practices needed. This job ad was AI-translated from German. See original About the job What to expect Exciting and innovative GenAI projects for our clients: from creative workshops to proofs of concept to joint implementation of productive solutions Design and implementation of LLM-based applications Design and implementation of Retrieval-Augmented Generation systems (RAG) Implementation of structured information extraction from unstructured documents Design and realisation of agentic systems and AI workflows Prompt and context engineering for targeted control of LLM-based solutions Careful evaluation of your solutions according to the principle of Evaluation Driven Development (EDD), including observability via AI evaluation and observability platforms You also contribute your expertise during the proposal phase and help shape offers professionally Optional touchpoints with classic software engineering and MLOps: where it makes sense, you work closely with our software and ML engineers Continuous learning and ongoing training in the field of GenAI as well as insights into the various industries of our clients Variety and exciting collaboration in internal project teams as well as on site with our clients What you bring Several years of experience in developing GenAI applications, ideally in productive use for clients or own products A completed bachelor’s degree in computer science, data science or a related field Proven expertise in implementing and operating Retrieval-Augmented Generation systems (RAG) Experience with agentic systems and AI workflows as well as the Model Context Protocol (MCP) Careful handling of the evaluation of LLM solutions, familiar with Evaluation Driven Development (EDD) and AI evaluation and observability platforms (AEOPs) Familiar with modern vector databases, e.g. Qdrant, as well as embedding and re-ranking models Understanding of open-weight large language models, including multimodal models Experience with LLM runtimes as well as LLM proxies or gateways Confident handling of Python and software engineering best practices Strong communication skills and enjoyment of collaboration with team and clients Fluent German and English, both spoken and written Advantageous: cloud experience in Infrastructure as Code (IaC), ideally Azure, as well as experience with guardrailing of LLM applications We are looking for you – become part of our team