About the job

AgentixLake GmbH · Hamburg, Germany

Remote within UAE

• https://www.linkedin.com/company/agentixlake/Help turn AI ideas into systems people can rely on.An AI application needs more than a convincing first answer. It needs relevant data, useful tools, measurable quality, and reliable software behind it.At AgentixLake, you’ll help build that software. We’re looking for a Working Student in AI Engineering who enjoys Python and wants to develop practical applications using large language models.About AgentixLakeAgentixLake is a Hamburg-based data and AI engineering company. We build production-grade data platforms and AI systems on our customers’ cloud and on-premises infrastructure.Our projects include AI agents that investigate data pipeline failures, assistants that answer questions using governed business data, and document intelligence systems that extract structured information from complex manuals.We are an AWS and Anthropic Certified Services Partner.What you’ll work onWorking alongside experienced engineers, you will:Help develop Python applications that connect large language models to data, APIs, and tools.
• Build and improve retrieval-augmented generation (RAG) workflows, including document processing, chunking, embeddings, and retrieval.
• Support document intelligence pipelines that extract structured, source-linked information from complex documents.
• Implement and test agent workflows, including tool use and human approval steps.
• Create evaluation datasets and compare answer quality, retrieval performance, latency, and cost.
• Add tests, logging, and documentation to make AI applications easier to operate and improve.

• What you bringPractical Python skills with APIs, JSON, and Git.
• Good understanding of large language models and curiosity in how AI applications are built.
• A careful approach to testing: you understand when a system works, when it fails, and why.
• Good English communication skills.

• Show us what you got: a university or personal project involving LLMs, RAG, embeddings, or AI agents; experience with Amazon Bedrock, Claude, vector databases, FastAPI, Docker, or an AI application framework.What you can expectExposure to the full application lifecycle, from experimentation and evaluation to deployment and monitoring.
• A small team where your questions, ideas, and contributions matter.