Full Stack Engineer (m/f/d)
GlassdollarAbout the role
TL;DR Join GlassDollar and help build the system some of Europe's largest companies use to find, test, and adopt startup technology. We're looking for an engineer who wants considerably more responsibility than "implement what's in the ticket". You'll take an ambiguous problem, shape it together with product, make the important technical decisions, ship it, and stay close enough to see whether it worked. We expect you to have opinions. We also expect you to be good enough to change them. The problem we're solving Large organisations are remarkably good at accumulating problems. A company with 100,000 employees can have thousands of operational challenges across its business units. Somewhere outside that organisation, a startup has probably already built part of the solution. Getting those two things to meet still happens through spreadsheets, long email threads, and meetings whose primary output is another meeting. GlassDollar OS is the operating system for venture clienting: problem → startup discovery → evaluation → PoC → adoption, in one repeatable workflow. Our customers are some of Europe's largest organisations, so the software has to move quickly and behave like something an enterprise can depend on. That tension creates the interesting engineering problems. What we're looking for You can take a problem further than the ticket. Work often starts with something incomplete, like "customers need a better way to manage X". You'll shape the problem with product, challenge assumptions, and decide what belongs in this iteration. Strong opinions about what we build, not only how, are expected here. You care about product. You want to know who you're building for, why the problem matters, and what success looks like. That context should shape your technical decisions. You have technical judgement. There is rarely one correct architecture. You know when the boring solution beats the ambitious one, when an abstraction helps and when it hides the problem, and when a small feature is about to create six months of technical debt. We expect you to reason about API boundaries, data models, permissions, performance, failure modes, testing, observability, and rollout, and to raise concerns with a clear argument attached. You make the system better, not just the feature. You fix the spreading pattern rather than the single instance, make an API easier for the next person, and improve tests because the current setup makes everyone afraid to deploy. Your impact should show beyond the pull requests with your name on them. You can work across the stack. A feature might run from a React interaction through GraphQL into a Node service, a schema redesign, a permissions update, and a safe migration for existing customers. Curiosity to follow the problem matters more than equal depth everywhere. You own quality. We have QA. That's not where quality begins. What breaks if this request happens twice? What happens with old data, or when the API fails halfway through? We
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