at Plancraft · 51-100 employees
Plancraft is an AI-first cloud SaaS that digitizes and automates administrative workflows for small construction and craft businesses with voice-enabled quoting, invoicing, time tracking, and site documentation.
OUR PURPOSE AT PLANCRAFT Building the backbone of European trades together – with AI-first software. We’re not just building software – we’re on a mission to create space for contractors & tradespeople by equipping them with AI solutions that work the way they do: fast, practical, and AI-first. With Tier 1 Investors from Europe and the US, like Headline and Creandum as well as 30,000+ tradespeople as customer base, we’re scaling across Europe to turn scattered tradespeople into thriving communities. We believe in zero admin, not zero personality – and we build every feature with the people in mind who wear the boots, not the suits. We’re #stoked to shape the future, #together as a team, and #humble in our mission to support the builders of tomorrow. YOUR MISSION AT PLANCRAFT We're building plancraft towards an agentic-first product experience. That means AI-enabled capabilities our customers actually use: features that take real administrative work off a tradesperson's plate and hold up under production load, day after day. Building AI-enabled products that work reliably at scale requires strong engineering foundations. You'll help shape those foundations — from architecture and system design to engineering practices — while keeping the focus on what we're ultimately building for our customers. This is an individual contributor role with no disciplinary leadership but significant influence across Engineering. You'll work hands-on where it matters, shape technical direction across teams, and help other engineers build better systems. We have a clear vision for how we want to build software and the outcomes we want to achieve, while recognising that we're still on the journey to get there. Some foundations are already in place; others are still evolving. We're looking for someone who has built and scaled complex systems before and can bring that experience into what we build. Our customers are tradespeople. Every hour they spend on paperwork is an hour off the job site. We keep that in mind when making technical decisions: the systems we build should ultimately help us take more work off their plate. YOUR RESPONSIBILITIES - AI-enabled product capabilities. You'll help define what AI can meaningfully do for our customers and turn emerging capabilities into reliable, observable product experiences that work beyond the demo. - The wider technical system. Together with our other Staff Engineers, you'll shape architectural direction and the properties that should hold across teams, while enabling individual teams to build and ship independently. - Data foundations for AI-enabled workflows. You’ll help turn product and business data into meaningful signals, insights, and context that AI can use reliably in customer-facing workflows — from defining the right data models and semantics, and drawing a clear line between operational data and knowledge, to making that understanding available where it creates real product value. - How we build with AI. You'll influence both how we develop and evaluate customer-facing AI capabilities and how AI changes software engineering itself — from tooling and workflows to standards and practices across the organisation. HOW YOU'LL WORK & INFLUENCE We have clear engineering principles, but we expect our Staff Engineers to challenge and evolve them. We favour small, integrated changes, observable systems that recover quickly, explicit architectural boundaries, and engineering decisions that are encoded rather than repeatedly debated. Above all, engineers own customer problems — not tickets. You'll have meaningful autonomy from the start: - Shape technical direction. You'll evolve shared architecture and engineering standards through RFCs and ADRs, not by waiting for top-down decisions. - Own complex initiatives end to end. From discovery and technical design through implementation, monitoring, and continuous improvement. - Influence where Engineering invests. You'll help identify the technical capabilities, architectural improvements, and engineering practices worth investing in. - Raise the bar across teams. You'll shape architecture, developer experience, AI-enabled engineering practices, and codebase quality beyond your immediate team. - Multiply other engineers. You'll mentor through collaboration, architectural guidance, code reviews, and knowledge sharing. How hands-on you are depends on the problem. Some weeks you'll be deep in the code; others you'll focus on system design, technical discovery, or mentoring across teams. We care about the technical outcomes you create, not your commit count. YOUR PROFILE - Experience building and operating real production systems. You've designed, shipped, and lived with complex systems at scale — whether distributed architectures, asynchronous or multi-step workflows, event-driven services, data pipelines, or ETL pipelines. You understand reliability and observability because you've needed them in practice. You bring 5+ years of software engineering experience and a track record of technical leadership. - Strong typed-language fundamentals — and a polyglot mindset. You understand the concepts that make a strong type system valuable and use them to keep a growing codebase understandable and maintainable. Our stack is React on the frontend, serverless Node.js / Express on the backend, and GCP underneath — all TypeScript, so you're either productive in TypeScript or able to get there quickly. Where your deepest expertise sits matters less: if that's Rust, Go, Kotlin, or something else, we see it as a strength. Having worked across several languages and paradigms tends to reduce stack bias exactly when systems thinking matters most. Experience with another modern cloud environment is absolutely fine. - Information systems thinking. You distinguish clearly between operational data and knowledge — the transactional state that runs the business versus the modelled, contextual under