Beschreibung
Thorit GmbH · Böblingen, Germany · Hybrid, mostly on-site · Working student (Werkstudent), 15 to 20 hours per week · Start as early as possible About the Role You'll build the agent stack an AI consultancy runs on. We use several LLMs across many internal tools, and today each one is wired up differently. You'll turn that into one LangChain foundation: one model-agnostic layer, shared building blocks and proper tracing, then move our internal tools onto it.
Real users, real production, from your first month. What You'll Do Map every internal tool that uses an LLM: which model, how it is called, what data flows through it Build our internal LangChain and LangGraph reference stack with a model-agnostic LLM layer, tool calling, MCP and structured outputs Migrate existing internal tools and agents onto that shared stack Compare LLMs with evals and tracing and help decide which model fits which use case Create templates and docs so colleagues build new tools the same way, including apps that started in Lovable Connect the stack to our systems through APIs, webhooks and a shared data model What You Bring Must-haves Enrolled in a computer science, software engineering, AI, data science or business informatics program At least one project you built yourself with LangChain or LangGraph (show us the code) Hands-on experience with more than one LLM or provider and an idea of their trade-offs Solid Python, plus first experience with REST APIs and SQL Very good English; German is a plus f
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