Product Engineer / Ex Technical Founder

Own the modules of the operating system for commercial production end to end. Understand every layer it touches, pull the experts together, and ship something customers pay for and love. You'll hold the whole thing in your head, decide what to build from a thin spec, and drive it across every discipline until it's done.

What you'll do

• Own modules end-to-end from customer requirements to shipped, paid-for product. The outcome is yours.
• Orchestrate across disciplines– get hardware, ML, agronomy, and AI engineers aligned and moving, and earn their trust by genuinely understanding their work.
• Talk to customers directly– understand what they need, decide what to build, and measure whether it worked.
• Build when it's the fastest path– prototype, integrate ML into the product, ship full-stack features, unblock yourself in unfamiliar territory.
• Make things happen– close the loop after shipping, don't just hand off a spec.

What you'll need

• Founded or co-founded a company, or owned a product like a founder would– built it, shipped it, and lived with the consequences.
• 3+ years building/managing production software. Strongly familiar with at least one backend and one frontend technology.
• Good at talking to users and turning fuzzy needs into something concrete. Most customers speak German.
• Can go deep across unfamiliar disciplines– hardware, ML, customer workflows, cloud ops far enough to make good calls and keep experts moving.
• Habitual AI power user (Claude Code, Cursor, Codex, or equivalent). Strong opinions on AI-augmented engineering.
• Can explain technical trade-offs to engineers and non-engineers alike, and know when to cut corners and when to be rigorous.

Nice to have

• Background or genuine curiosity in agriculture, climate, or deep tech/hardware.
• Experience interfacing ML or CV into a real product.
• Worked close to hardware or physical systems before.

What they offer

• Full ownership of modules customers actually pay for.
• Team of genuine experts across hardware, ML, AI, and agronomy.
• Berlin, hybrid.
• Equity and perks.