Senior Data Engineer - AI Focused

TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization. We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact? Responsibilities We are seeking a skilled and detail-oriented Data Engineer to join our growing team. In this role, you will be responsible for designing, building, and maintaining the systems that collect, store, and prepare data for analysis across the organization. Your work will serve as the foundation for our data-driven decision-making and AI initiatives, making you a key enabler for our analytics and AI teams. Design and implement scalable data models and storage structures to support AI applications, including LLM workflows, retrieval systems (RAG), and feature generation across data warehouses, lakes, and vector databases. Build, maintain, and optimize robust data pipelines (ETL/ELT) in Python to ingest, transform, and serve data for both traditional analytics and AI/LLM-driven use cases. Develop and orchestrate end-to-end AI data workflows, including ingestion, embedding generation, indexing, and retrieval, using workflow orchestration tools to ensure reliability and performance. Implement and manage data retrieval pipelines (e.g., RAG), including chunking strategies, embedding pipelines, vector storage, and query optimization for high-quality LLM outputs. Define and enforce data quality standards across both structured and unstructured data, ensuring integrity, consistency, and relevance for downstream AI applications. Build monitoring and observability systems for AI pipelines and LLM interactions, including tracking latency, cost, quality, and failure modes. Design and implement CI/CD pipelines for AI systems, enabling automated testing, validation, and safe deployment of changes to data pipelines, prompts, and models. Establish and maintain data governance, security, and compliance practices, including access control, encryption, and handling of sensitive data in AI workflows (e.g., GDPR considerations). Develop and maintain scalable data and AI platforms that support experimentation, evaluation, and deployment of machine learning and LLM-based systems. Collaborate closely with AI Engineers, Software Engineers, and Product teams to translate business requirements into reliable, production-ready AI and data solutions. Requirements Experience building production-grade data pipelines and AI systems (as an AI Engine