Founding AI Engineer

🚀 Founding AI Engineer | High Growth Startup | Lisbon or Remote You will own the AI product that takes over the planning of real estate projects, one of the last major processes that still runs almost entirely by hand. Today there are prototypes and internal scripts. The architecture behind them will be built in this role: model selection, agent systems, retrieval, document processing and the evaluation foundation underneath. Together with the founders, you will take it from discovery on real projects to your own prototype and on to a measurable commercial result. Who we are Planeco is the AI native architecture firm for the German market. We are building the infrastructure that digitizes planning and permitting for real estate projects of every size, end to end: faster, cheaper and scalable. To do this, we combine our own architects with an external partner network and a tech and automation layer that optimizes or fully replaces many manual processes. We build everything, from carports and Airbnb conversions to large apartment buildings and padel halls. 3,000+ projects per year across Germany15 to 20% MoM growth as a bootstrapped ventureProfitable, with a run rate above €10MYoung team of 40+ ambitious people What we offer A testing ground of 3,000 projects a year: Real estate projects of every size, real cases with clear outcomes. You see the effect of your work in the same week, in hours per project and turnaround time.Domain experts in house: Architects and specialist planners work at the same location. Ground truth comes from a conversation rather than from research.Access instead of approvals: You work directly with the founders, with no layers in between. Decisions are made in conversation, and you get production access from your first week.Budget for models and tools: API costs, Cursor, Claude Code and hardware of your choice. Inference costs in the hundreds of euros are not up for debate when there is an experiment behind them.VSOP included: We are bootstrapped and profitable, so there is no board theater and no fundraising quarters. Our runway comes from customers.Your own team down the line: As automation grows, a team will form around it. The lead for this unit will be filled internally, not hired externally.Lisbon or remote: Work from anywhere in DACH or join us at our Lisbon office, where our chef cooks healthy lunch and dinner three times a week. Your responsibilities Product ownership: You own the AI products along the permit planning process, from the first project idea to the submitted plans. You take them from hypothesis and experiment to production use in more than 3,000 projects per year.Building first: Every initiative starts with your prototype, a working end to end slice rather than a presentation.Technical vision: You design the data model and system landscape. You decide which steps run fully automated, which keep a human in the loop and which deliberately stay manual.Use case prioritization: You prioritize by business impact, technical feasibility and value for customers and the planning team. You measure it in hours per project, turnaround time and margin.Evaluation foundation: You set up test cases, error classes and regression protection. You make model quality visible so decisions are based on data.Roadmap and capacity: Scope, sequencing and the quality bar come from you. Agencies contribute where capacity is needed rather than judgment.Rollout with the planning team: You introduce solutions together with architects, specialist planners and project management, and you prove the impact with numbers.First quarter goal: A process step that is manual today runs automated, is measurable and has been handed over into day to day operations. You're a great fit if you hold a degree in computer science, information systems, data science, engineering or a comparable field. How you got there matters less to us than what you built afterwards.have at least three years of experience as a Product Manager, AI Product Manager, Founding Engineer or in a comparable role with real product ownership.have run your own products in production with real users, from idea to live operation. Side projects count just as much as professional work.write code yourself: you write and debug Python, read unfamiliar codebases, connect APIs and use the terminal as your working environment.know LLMs, agent systems, retrieval and document processing from hands on use, not from articles.are analytically honest and ground your hypotheses in data. Industry knowledge can be learned. Turning a model into a tool for daily operations is much harder. Apply now if you want to shake up the construction industry with us!