> Markdown version of [/jobs/ext/2422220-working-student-ai-product-engineering-data](https://www.wearedevelopers.com/jobs/ext/2422220-working-student-ai-product-engineering-data). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Working Student: AI Product Engineering - Data - **Company:** Retorio Gmbh - **Location:** München, Germany - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Python (Programming Language), Software Product Management, SQL Databases, Large Language Models, Data Layers, Information Technology - **Published:** August 31, 2026 - **Apply:** https://www.careerjet.de/jobad/de908c967d6ff1814186627ae865424b65 ## About the Role * Enrolled student in Computer Science, Data Science, or a related field * Comfortable with SQL and Python * You think in products, not tickets: you care what a feature does for the user, not just that the code runs * Genuinely into agents, LLMs, MCP, and the current wave of AI tooling * You like clean data and shipping things that work * Comfortable working in English ## Description About the role (Munich, onsite, ~20 hrs/week, 5 months): You own our data layer. The tables, views, and pipelines that answer the questions we keep asking are yours. Every time we change logic or launch something, we see the clean before-and-after instead of digging by hand. On the product side, you take ideas from our roadmap and turn them into shipped features, with AI agents and the newest tooling as your accelerators. This is build-the-future work, not ticket-closing. Tasks * Building our analytics and metrics layer from the ground up: version-controlled metric definitions, tested transformation models, and pipelines that both humans and our AI can query * Pulling outside sources in and tying them to product behavior, so every launch and logic change is measurable * Building product features end to end with our engineering team, from data model to shipped result * Using AI agents, MCP, and tool-calling to multiply what you can build, including agents that drive and test the product like a real user * Making product decisions with our PM, building them, and owning the outcome ## Related Videos - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Why Your AI Agent Keeps Hallucinating Your Data: Building Deterministic Context Layers](https://www.wearedevelopers.com/videos/2055-why-your-ai-agent-keeps-hallucinating-your-data-building-deterministic-context-layers) - [Creating Industry ready solutions with LLM Models](https://www.wearedevelopers.com/videos/899-creating-industry-ready-solutions-with-llm-models) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [How to govern Vibe Coding for the Enterprise](https://www.wearedevelopers.com/videos/100290-how-to-govern-vibe-coding-for-the-enterprise) - [Building Products in the era of GenAI](https://www.wearedevelopers.com/videos/827-building-products-in-the-era-of-genai) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Best Coding Boot Camps in Germany](https://www.wearedevelopers.com/magazine/237-best-coding-boot-camps-in-germany) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)