AI/LLM Engineering – Working Student

📋 Description

• Design and enhance agentic workflows (including tool/function calling, planning, self-checks) for analytics, summaries, visualizations, and task automation.

• Create adapters and tools to connect LLMs with both internal and external services.

• Contribute to our FastAPI backend by implementing clean interfaces, Pydantic validation, and thorough testing.

• Develop evaluation metrics to assess accuracy, latency, and cost-effectiveness.

• Refine prompts, retrieval/contexting, and execution strategies to ensure privacy, reliability, and performance.

• Deploy services in containers (Docker) and collaborate on deployment strategies (Kubernetes), CI, and observability.

• Document technical decisions and share insights with the team.

⛳️ Requirements

• Proficiency with LLMs/AI agents (function/tool calling, RAG, MCP, or agent frameworks) along with a solid foundation in Machine Learning.

• Strong Python programming skills for production code and data-related tasks (including type hints, tests, and packaging).

• Familiarity with APIs and microservices (preferably FastAPI), Git, and container-based development (Docker).

• Excellent problem-solving abilities, effective communication skills, and a proactive ownership approach.

• Currently pursuing a degree in Computer Science, Data Science, AI, or a related field and eligible for working student positions.

• Nice to have: experience with retrieval/RAG stacks (embeddings, chunking, evaluators), Redis, PostgreSQL.

• Familiarity with Kubernetes, GitLab CI, and observability tools (logs/metrics/traces).

• Experience with React/TypeScript for lightweight UI development.

• Interest in EU privacy/GDPR and safety-by-design principles for enterprise AI.

• Exposure to self-hosted/open models (e.g., Llama, Mistral) and model serving techniques.

• Understanding of knowledge-graph concepts and graph query languages.

🏝️ Benefits

• Engage in impactful, privacy-first AI projects with genuine enterprise pilots.

• Accelerate your learning with close mentorship from a team of experienced AI professionals.

• Enjoy flexible working hours, a remote-friendly environment, and make a meaningful impact from day one.

• Receive competitive compensation as a working student.