Responsable Técnico de Segmento Terrestre para Constelaciones de Satélites

At MAGNOTHERM, we are developing a revolutionary refrigeration technology that has the potential to eliminate up to 30% of energy demand and 100% of direct greenhouse gas emissions in the cooling industry. Our vision is to provide the cleanest and most sophisticated cooling solutions to reduce climate impact and costs. Founded in 2019, our deep tech company is a spin-off of the Technical University of Darmstadt.

MAGNOTHERM is scaling up its engineering organization to build superconducting magnetocaloric cooling. As we grow, the company's information backbone must grow first — and we're building it, not buying it. You are that backbone: one person, amplified by AI agents, who does what traditionally took an entire IT department. You'll run our infrastructure, build our internal tools, make our company knowledge agent-accessible, and teach the team to work agentically. This role did not exist five years ago anywhere.

What you’ll own:

• Agentic toolchain (core mandate). Design and build the company's internal tool suite — PDM/BOM and engineering-change management, knowledge base, procurement & inventory, controlling & budgeting, test- and quality-data traceability with per-unit records, hiring pipeline, CRM, project & program tracking, asset & lab management with calibration schedules, and time & resource planning — as open-source + custom builds, developed with and operated by AI agents. Build-not-buy is the explicit company decision; you make it viable.
• Company knowledge as a system. Structure our documentation, engineering data, and decisions so LLMs can use them: RAG pipelines, MCP servers over internal systems, and custom agents/assistants the whole team queries daily. You own knowledge continuity — what we learn must outlive any single laptop or head.
• Infrastructure & IT. Classic sysadmin scope, run agentically: servers, networking, identity & access management, endpoint management, backups and disaster recovery, security — including an on-prem server as well as external resources for LLM inference. You are the human accountable for access control and production changes; agents do the routine work.
• Engineering-team leverage. Streamline the toolchains our engineers build and use — test-bench data pipelines, automated test reporting, live rig‑telemetry dashboards, and simulation batch workflows. Harden the quick tools engineers write into maintained ones.
• Enablement. Every engineer gets an LLM budget; you make it pay off. Run internal training, build playbooks and shared agent configurations, and raise the whole team's agentic‑engineering baseline.
• UX of internal tools. Internal tools people hate don't get used. You apply our design system and basic UX craft so the tools you ship are ones a production technician actually opens.

What you would ideally bring to the table

Must‑have skills & experience

• Software generalist: strong Python and/or TypeScript, full-stack comfort (simple web apps, APIs, databases), 4+ years building real systems — internal tools