Working Student AI Engineer – LLMs, RAG & AI Agents

Develop Python services and integrations connecting language models to enterprise data, APIs and tools.

Implement document ingestion, chunking, embeddings and retrieval, with source references that users can inspect.

Build structured extraction and validation workflows for complex documents and downstream business systems.

Implement defined agent steps, including tool calls, permission checks, error handling and human approval.

Maintain evaluation cases and compare retrieval quality, answer usefulness, latency and cost as the application changes.

Contribute automated tests, deployment configuration, logging and documentation through reviewed pull requests.

What you bring

Current university enrolment in computer science, AI, data science or a related technical discipline.

Strong practical Python skills and evidence of software you have delivered for actual users, including responsibility for testing and deployment.

Hands-on experience with an LLM application involving retrieval, tool use or structured outputs, and the ability to explain its limitations.

Comfort working with APIs, JSON, Git and code review, and taking a defined task from an agreed requirement to a maintainable implementation.

Clear English communication and an evidence-based approach to debugging and evaluating system behaviour.

Experience with Amazon Bedrock, Anthropic Claude, FastAPI, Docker, vector databases or self-hosted models is valuable. We value sound implementation decisions more than the number of frameworks on your CV.

What you can expect

You will contribute to real delivery work with direct access to experienced engineers and the founders. Expect clear ownership, thoughtful code review and a part-time scope planned around your studies.

How to apply

Use the Apply button on this page to submit your CV, current study details, location and weekly availability. Explain one AI application you built, your individual contribution, how you evaluated it and what you improved after testing. An anonymised description is welcome; please do not share confidential client material.

We welcome applicants of all backgrounds. If the core responsibilities match your experience, we would like to hear from you.

Stay connected

Follow AgentixLake on LinkedIn for practical engineering insights, project updates and future opportunities. Following is optional and does not influence recruitment decisions.

LinkedIn: https://www.linkedin.com/company/agentixlakegmbh/

Website: https://agentixlake.com/

Explore our production AI work with Claude: https://agentixlake.com/production-ai-with-claude

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