Expertise is the bottleneck in technical field service. We are building the AI that makes it scale – and learns from every visit, from every job.
Stealth-mode AI venture building a copilot that guides technicians at every job like an experienced master craftsman – before, during and after every job
Built in the field, not behind closed doors: our product is developed with direct access to thousands of technicians with a leading European real estate industry partner – every feature is tested on real jobs, with results in days instead of months
Backed by Founders Factory; founding team in Berlin, MVP built and tested with technicians, now heading towards spin-out and first funding
Vision: Europe’s leading field service intelligence layer.
We have built and tested our MVP. Now we are looking for a hand-on Co-Founder & CTO who builds the technology and product that grows and scales the company.
Own the technology end to end: architecture, roadmap, build-vs-buy decisions, reliability and security
Take the tested MVP to a production-grade product used daily by technicians in the field
Build reliable AI workflows and repeatable integrations into customer systems such as work orders and asset data
Continuously improve the Machine Learning core: retrieval over manufacturer and expert knowledge, multimodal input (photo, voice) and diagnostic reasoning
Design and build the learning engine that makes the product smarter with every visit: capturing, reviewing, evaluating and reusing confirmed outcomes – the core of our knowledge moat
Set up evaluation, safety and monitoring: expert-reviewed benchmark cases, grounding, escalation and regression testing
Build a state-of-the-art UX/UI that technicians want to use every day
Spend time with technicians in the field and turn their feedback into product within days
Recruit and lead the engineering team as we scale
Shape the company as a co-founder: strategy, culture and investor conversations alongside the founding team
Master’s degree in Computer Science, Machine Learning/AI, Data Science, Mathematics, Physics, Electrical Engineering or a related quantitative field
Machine Learning experience, ideally 3+ years applying it in production products (e.g. LLMs, retrieval/RAG, NLP, computer vision, model evaluation)
Entrepreneurial mindset: you want to build a company, not just a product – full ownership, bias for action and comfort with ambiguity
Experience leading the technical build of a product from zero to one, e.g. as tech lead or founding engineer
Strong hands-on software engineering across backend, APIs, data pipelines and cloud – you still build and ship yourself
Sound technical judgement: you know the limits of LLMs, how to test them and when not to use them
Product empathy: you enjoy learning from users in the field and making complex work simple
Fluent German and English – German is needed for working with technicians and technical source material
PhD in Machine Learning, NLP, Computer Vision, Information Retrieval or a related field
Previous founder or early-stage startup experience
Experience with Microsoft Azure and enterprise B2B requirements (security, GDPR, multi-tenant SaaS)
Background in field service, industrial, maintenance or proptech software
Experience with multimodal AI, voice interfaces or decision-support systems
Experience hiring and leading engineering teams
Competitive compensation package, including a meaningful co-founder equity stake
A true co-founder role with ownership of the technology and a real say in the direction of the company
An unfair head start: a cooperating partner with thousands of technicians and real repair data from day one – the fuel for a system that learns from every job
A tested MVP and a clear path to spin-out and funding
Support from Founders Factory’s network across tech, design and growth
A mission with real-world impact: helping close the skilled-trades gap in Europe
Berlin / hybrid, flexible
Full-time; start as soon as possible
Send your CV or LinkedIn profile with a short note on why you want to build this company with us and an example of Machine Learning work you have shipped