Junior KI-Projektbegleiter & Trainer (w/m/d)

Role overview

Junior AI Project Companion & Trainer (w/m/d) in Munich (hybrid), with 20h/week dedicated to AI projects plus AI trainings. You will both run customer trainings and support real customer projects—from early ideas to implementation—working in a small, agile team with flat hierarchies.

Start: no later than early October 2026 (otherwise the role must be filled externally).

Responsibilities

• Prepare and deliver basic AI trainings independently for customers across industries and skill levels (beginner to advanced)
  • Topics include Prompt Engineering, tool introductions, and AI fundamentals
• Support ~20 hours/week on AI projects, including:
  • onboarding phase: first 3 months mainly in the background to ramp up
  • later: increasing ownership and responsibility
  • help with conception, requirements analysis, customer workshops, and technical translation
• Moderate customer workshops: capture requirements, outline solutions, and communicate AI potential
• Support Agile delivery across the path prototype → MVP → scalable product with consultants and engineers
• Apply modern AI tooling in practice, including:
  • n8n, LangChain, RAG, LLM-based APIs, vector databases (e.g., Pinecone)
  • Notion AI, Make
• Create enablement materials and documentation:
  • handouts, videos, guides (for customer adoption)
• Support customers with AI tool adoption—not just explaining, but empowering users

Requirements

• 1–2 years of professional experience after studies in tech / agency / consulting (intended for real career starters; not suitable for fresh grads without experience or pure student roles)
• Experience managing or contributing to customer projects (small internal initiatives also count)
• Strong understanding of AI and ML processes and their practical application (Data Scientist level not required, but you must understand what AI can and cannot do)
• Practical experience with tools such as n8n, Make, RAG, LLM-based APIs, Notion AI (hands-on, not “from hearsay”)

Nice to haves

• Tech-narrow or AI-related content experience (ideal): e.g., customer-facing projects or close-to-tech initiatives