Public summary
Join an AI-first energy transition company based in Berlin to design and automate internal workflows across Ops, Energy, Sales, CS, and Finance teams. Build end-to-end AI-powered agentic systems using Python and TypeScript, create integrations with tools like HubSpot, Slack, and Notion, and deploy production-quality internal tools. Work closely with multiple departments to identify and implement automation opportunities, contributing to real impact in a fast-growing startup environment. This is an office-first internship offering hands-on experience in cutting-edge AI automation within the energy sector.
Location and work setup
- Location
- Berlin
- Remote status
- On-site
- German requirement signal
- Unclear
- Detected job language
- English
Responsibilities
Design, build, and deploy agentic AI systems, RAG pipelines, and prompt engineering that automate high-volume internal workflows. Develop and maintain custom MCP servers and integrations connecting enterprise tools (HubSpot, Slack, Notion, Aircall). Write production-grade Python and TypeScript code with strong schema design and security. Own internal tooling lifecycle from identification of needs to deployment on platforms like Firebase, Vercel, or Google Cloud Platform with CI/CD workflows. Build AI-native skills and plugins to onboard colleagues to automated workflows. Collaborate across Ops, Energy, Sales, Customer Success, and Finance departments to prioritize and implement automation solutions.
Qualifications
Experience shipping AI-powered tools, agentic systems, or RAG pipelines via projects, hackathons, or work. Skilled in production-level Python and/or TypeScript programming with knowledge of trade-offs. Comfortable integrating REST APIs, webhooks, and authentication for third-party applications. Proactive problem solver able to identify gaps and deliver solutions independently. Based in Berlin with preference for office presence. Bonus if experienced with MCP, Claude Code, LangChain or similar AI frameworks. German language skills (B1+) are advantageous but not mandatory.