Founding Engineer (working student/intern) - AI, RAG & Pattern Recognition

As a Founding Engineer (working student/intern) at LeadLane, you will help build the technical foundation of an AI sales platform for complex B2B products from day one. You will take ownership of architecture, RAG systems, LLM integration, and ML components-working directly with the founders. This is a role for doers who want to truly shape technology.

Activities

• Development of an AI-supported MVP for a sales platform with a focus on complex B2B products
• Establishment of a Retrieval-Augmented Generation (RAG) system with vector databases and LLM connection
• Integration of open language models (e.g., LLaMA 3, Mistral, Command R+) to generate pitches, use cases, and demos
• Development of ML components for pattern recognition in customer data, lead behavior, and use cases
• Support in building a modular, scalable architecture (backend, API, databases)
• Designing MVP-like frontends (e.g., with React/Next.js) for visualizing results
• Collaborating with founders, SDRs, and external data scientists-you'll be right in the thick of things

Requirements

• You are a registered student in a master's or advanced bachelor's program in computer science, software engineering, data science, or a comparable field
• Strong programming skills in Python (e.g., FastAPI, LangChain, ML toolkits) and/or JavaScript/TypeScript
• Experience with APIs, databases, Git, Docker - ideally also with vector databases (e.g., Weaviate, Pinecone, Qdrant)
• Initial practical experience in the field of LLMs, embeddings, prompt engineering, or RAG is a big plus
• Interest in or experience with pattern recognition/machine learning, e.g., with scikit-learn, PyTorch, spaCy, or similar libraries
• You have a product-driven mindset - MVP first, clean iteration, quick validation
• You are communicative, pragmatic, and love ownership: "Give me the problem, I'll ship the solution."
• Very good English skills (German is a plus, but not a must)

Application Process

Our application process consists of three stages:

1. Initial meeting - a relaxed conversation in which we introduce ourselves to each other and find out whether our expectations match.
2. Case study - you will be given a small technical task to help us better understand your approach, ownership, and way of thinking.
3. Team meeting - finally, you will get to know the team and can ask any questions you may have about working together and our culture.