Working Student AI Engineer – LLMs, RAG, AI Agents

This is a fully remote position, open to applicants in Germany.

📋 Description

• Design and develop Python services and integrations that connect language models with enterprise data, APIs, and tools.

• Execute document ingestion, chunking, embeddings, and retrieval while ensuring inspectable source references.

• Create structured extraction and validation workflows tailored for complex documents and downstream business systems.

• Implement defined agent steps, which include tool calls, permission checks, error handling, and obtaining human approval.

• Maintain evaluation cases to assess retrieval quality, answer relevance, latency, and associated costs.

• Contribute to automated testing, deployment configurations, logging, and documentation through peer-reviewed pull requests.

• Collaborate with team members on implementation, code review, and maintaining operational quality.

• Contribute to areas such as document intelligence, knowledge assistants, governed analytics, or AI agents.

⛳️ Requirements

• Currently enrolled in a university program focusing on computer science, AI, data science, or a related technical field.

• Proficient in practical Python programming.

• Proven experience in delivering software to actual users, including managing testing and deployment processes.

• Hands-on experience with an LLM application that involves retrieval, tool usage, or generating structured outputs.

• Capability to articulate the limitations inherent in an LLM application.

• Comfortable working with APIs, JSON, Git, and engaging in code reviews.

• Ability to transition a defined task from agreed requirements to a sustainable implementation.

• Proficient in English communication.

• Evidence-based approach to debugging and assessing system behavior.

• Familiarity with Amazon Bedrock, Anthropic Claude, FastAPI, Docker, vector databases, or self-hosted models is advantageous.

🏝️ Benefits

• 3-month probation period.

• 20 days of annual leave.

• Part-time work scope designed around academic commitments.

• Direct access to seasoned engineers and founders.

• Clear ownership of tasks and thoughtful code review process.

• Hands-on experience with real delivery work.

• Flexible work arrangements to accommodate university studies.