Responsibilities
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 Engineer, ML Engineer, or Data Engineer).
* Strong Python skills and solid SQL; able to design and implement reliable ETL/ELT workflows.
* Hands‑on experience with LLM applications, including building and operating RAG pipelines (embeddings, vector stores, retrieval).
* Familiarity with at least one cloud platform, either GCP or Azure, and relevant data/AI services.
* Experience with CI/CD and testing for data or AI systems.
* Practical understanding of monitoring (pipelines and LLM usage: failures, latency, cost, output quality).
* Comfortable working with Git and collaborative development workflows.
* Ability to work independently, debug complex systems, and make pragmatic engineering trade‑offs.
What we offer
* Onsite onboarding in our HQ office for an optimal start.
* An attractive compensation package above the collectively agreed minimum basic salary (according to the IT‑KV, Regelstufe with classification ST1/rule: EUR 3,724, with ST2/rule: EUR 4,346 gross/month).
* 28 days of well‑deserved holidays.
* Great benefits package including company achievement bonus and regular salary reviews.
* Special terms for local gyms.
* Access to Corporate Benefits platform with many discounts.
* Regular team events and company‑wide celebrations.
* Open‑door policy, no dress code rules, frequent All‑Hands and Leadership Lunches.
* Work from abroad program allowing up to 40 days of work outside your contracting country.
* We celebrate diversity as one of core values, join and drive one of the c‑a‑r‑e initiatives together with us!
TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We care and understand that our diverse, values‑driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.
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