Opis
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
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