Working Student AI Software Engineer, LangChain (all genders)
Overview
Thorit is offering a working student position for an AI Software Engineer focusing on LangChain, based out of the Böblingen headquarters in Germany. The role requires 15 to 20 hours per week with a start date as early as possible. The work mode is hybrid, mostly on-site, requiring the student to live close enough to Böblingen to work from the office at least one day a week.
Who can apply
Applicants must be enrolled in a degree program in computer science, software engineering, artificial intelligence, data science, or business informatics. Candidates need to show at least one self-built project using LangChain or LangGraph, possess hands-on experience with multiple LLMs or providers, and have a solid foundation in Python along with initial experience using REST APIs and SQL. Very good English language skills are required, while German is considered a plus.
What you get
The position offers flexible working hours designed around lectures and exam periods, with the option for increased hours during semester breaks. Additional benefits include pro-rata paid vacation based on a 31-day annual allowance for full-time positions, access to frontier large language models, code reviews by senior engineers, a MacBook, and a modern office in Böblingen equipped with free parking, public transport access, and company e-scooters. Employees also receive a tax-free lunch subsidy of five euros per working day, free snacks, fruit, coffee, and drinks, a dog-friendly office environment, Corporate Benefits discounts, and participation in team events and company offsites. Furthermore, students have the opportunity to write their thesis on an applied LLM or agent topic with the company, alongside a clear pathway to a Junior AI Engineer role following graduation.
Requirements
The role involves mapping internal tools using large language models, building the internal LangChain and LangGraph reference stack, migrating existing tools and agents, and evaluating models using tracing. Responsibilities also include creating documentation and templates, connecting the stack to systems via APIs and webhooks, and collaborating directly with internal users and senior engineering team members.