Working Student (f/m/d) LLM Wiki & Agentic AI Knowledge Systems

Kurz zusammengefasst

We are looking for a working student to join NXP's AI‑focused team and help create an LLM‑based Wiki that serves as a collaborative, AI‑native knowledge and working environment. The company develops complex subsidy programmes that blend regulatory rules, business processes, technical documentation, structured data and multi‑stakeholder collaboration, and now wants to transform how that knowledge is built, linked, maintained and applied by leveraging large language models and autonomous agents. In this role you will be responsible for building, configuring and continuously improving the LLM Wiki and its surrounding AI‑native knowledge platform. You will design AI‑readable structures, metadata, context, references, relationships, templates and workspaces, and experiment with context engineering, retrieval, knowledge curation and AI‑assisted content creation. You will develop and test AI agents that can search, connect, challenge, update and help create knowledge, while evaluating different LLMs, agent approaches and tools for specific tasks. You will also create controlled workflows that turn collaborative and AI‑generated output into reviewed, authoritative knowledge, testing for source traceability, permissions, context limits, outdated information and hallucinations. Direct interaction with pioneer users will be required to gather feedback, prototype new methods, and produce reusable templates, onboarding material, administration and governance practices. All architecture decisions, experiments, implementation choices and test results must be documented. The position requires you to be currently enrolled in a Bachelor's or Master's programme, preferably in computer science, IT, data science, information systems, business informatics or a related field, though practical experience is valued more than the exact discipline. You must have hands‑on experience with an LLM Wiki, AI‑native knowledge system, RAG environment, agentic workspace or a comparable solution, demonstrated through personal projects, university work or open‑source contributions. You need to be able to explain in detail what you have built, configured or used intensively, including successes, failures and lessons learned. Practical familiarity with modern LLMs and AI tools, prompting, context management, retrieval, agents or tool use, is essential, as are basic programming or scripting abilities to turn ideas into prototypes. A strong interest in structuring knowledge for both humans and AI, a methodical experimental mindset, and attention to source traceability, permissions, data quality, versioning, maintainability and safe AI use are required. You must be able to work independently while collaborating closely with domain experts and users, and you need fluent business‑level English. Nice‑to‑have experience includes working with Microsoft 365, Copilot, Claude, SharePoint, Microsoft Graph, Confluence, Jira, APIs, Python, Git, knowledge graphs, vector databases or retrieval systems. The role offers an hourly wage of €19.40, 30 vacation days, flexible working hours, on‑site canteen access and participation in various employee resource groups. Security‑related tasks may be part of the assignment, so a reliable, security‑aware work style is important. What the role asks for: - Currently enrolled in Bachelor's or Master's programme - Hands‑on experience with LLM Wiki or similar solution - Ability to explain built/configured system in detail - Practical experience with modern LLMs and AI tools - Basic programming or scripting skills - Structured, experimental mindset with focus on traceability - Fluent business English - Nice‑to‑have: experience with Microsoft 365, Copilot, Claude, SharePoint, Microsoft Graph, Confluence, Jira, APIs, Python, Git, knowledge graphs, vector databases, retrieval systems.