# Product Engineer / Ex Technical Founder at Hexafarms > Remote · Germany · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/personio%3Ahexafarms%3A2676772 (read 2026-11-09). ## Facts (observed) - Company: [Hexafarms](https://alderhq.app/companies/hexafarms) - Location text: Hybrid; Remote; Berlin - Where it can be done from (inferred): Remote · Germany (evidence: "Location: Hybrid; Remote; Berlin") - Posted: 2026-06-17 (144 days ago) - First seen by alder: 2026-11-04 · last verified: 2026-11-07 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://hexafarms.jobs.personio.de/job/2676772 ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Berlin, n 50): p25 €59k, median €69k, p75 €100k ## Description (the employer's text) ### Your mission 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 ???? ### About the role Our product offerings are made of modules– forecasting is one example, and there are many more. We're looking for a Product Engineer to own the product end to end. That means you understand every layer it touches– the hardware feeding it data, the ML behind its predictions, the agronomy that makes it correct, the software the customer sees– well enough to earn the trust of each expert, pull them together, and ship modules customers pay for. This is the role we couldn't fill with a traditional product manager. It needs someone who can hold the whole thing in their head, decide what to build from a thin spec, and drive it across every discipline until it's done. You won't write a lot of code– that's what the experts are for– but you're technical enough to prototype, glue the pieces together, and ship code yourself when that's the fastest path. 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. ### Your profile - You've 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. - You're good at talking to users and turning fuzzy needs into something concrete. FYI, most of our customers only speak German. - You can go deep across unfamiliar disciplines– hardware, ML, a gnarly customer workflow, cloud ops far enough to make good calls and keep experts moving. - Habitual AI power user (Claude Code, Cursor, Codex, or whatever's next). Strong opinions on AI-augmented engineering; always finding tools that make the team faster. - You can explain technical trade-offs to engineers and non-engineers alike, and you know when to cut corners and when to be rigorous. ### Nice to have - Background or genuine curiosity in agriculture, climate, or deep tech / hardware. - Some experience interfacing ML or CV into a real product. - You've worked close to hardware or physical systems before. ### Why us? The difference: you're joining a company with traction, paying customers, and a clear technical direction– and a hard, real problem worth owning. - Full ownership of modules customers actually pay for. - A team of genuine experts across hardware, ML, AI, and agronomy to build with. - Berlin, hybrid. - Benefits– equity / perks / visiting farms/ morning matchas/ strawberries, etc. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/personio%3Ahexafarms%3A2676772 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.