Product Engineer, Growth Acquisition

Mentimeter is an engagement tool with a clear goal in mind. To make every leader better. Through real-time interactivity and clear visualizations, we get people to participate, engage and become more productive. Transforming all those passive meetings, airless classrooms and drawn out trainings into valuable insights and impactful moments. We truly believe that you achieve the best results by doing things together. And that successful leaders need to adopt a curious and collaborative mindset in order to get there. So with you at Mentimeter, you’ll be a big part of the ambition to help over 1 billion people listen, learn and work better together. Why this role exists The web is changing. For twenty years, websites have been built around content management systems, where people manually create, edit, and publish every page. We think that era is ending. AI is changing how digital experiences are designed, built, optimized, and discovered, and websites are becoming composable systems built on structured content, reusable components, data, and AI. We’ve already started building that at Mentimeter, moving to a Markdown-based system with a bespoke CMS and agentic workflows. Now we’re looking for an engineer who’ll help us take it to the next level. Our website is our storefront. It’s where millions of people meet Mentimeter for the first time, and it sits in the middle of almost everything we do: product, marketing, sales, brand, search. Your job is to own the technical foundation underneath it and keep making it better at one thing: helping people find Mentimeter, understand it, and sign up. In practice, that means evolving the Growth Operating System—the platform that lets engineers, designers, marketers, copywriters, and AI agents work on world-class digital experiences together. This isn’t a job maintaining a marketing website. It’s building the machine that produces one. What you'll own You'll own the technical foundation behind web acquisition, and not only the building of it. You'll help decide what's worth building, ship it, measure it, and interpret what the results actually mean. Web platform Frontend architecture, the component library, deployment pipeline, performance, and the foundations everything else sits on. Growth Operating System The systems, workflows, and automation that let people and AI work together across the whole web lifecycle. Design systems, structured content, experimentation, analytics, and AI, connected into something coherent instead of a CMS with bolted-on features. Discoverability Technical SEO, structured data, AI search, and whatever comes next for being found, both by search engines and by AI assistants. Measurement and attribution Analytics, event instrumentation, server-side tracking, Conversion APIs, attribution and marketing measurement. If we can't trust the numbers, we can't learn anything from them. Experimentation The infrastructure behind fast experiments, personalization, feature flags and continuous optimization, and making that infrastructure usable by people who don't write code. Internal platform Tooling, automation and AI-assisted workflows that make life easier for marketers, designers, copywriters, editors and localization teams. Design system Working with Design on a component system that scales, stays consistent and accessible, and doesn't slow anyone down. AI enablement The knowledge and context layer that gives AI agents what they need to generate, improve, and localize content well. That includes turning product analytics, marketing data, and experiment results into context a model can actually use, and having the judgment to know when the output is good enough to ship. How you'll work We call this a Product Engineer role, and we mean something specific by it. Start with the outcome You'll work with our Growth PM, Design, Marketing, and Analytics to clarify the problem we're solving and how we'll know it worked before much gets built. If a brief doesn't hold up, we expect you to say so, and to bring your own ideas about where the leverage is. Finish the loop Get clear on the outcome, ship, watch what happens, learn, adjust. Shipping is the middle of the job, not the end. The experiment that failed is often more interesting than the one that worked, as long as somebody bothers to find out why. Be clear about trade-offs A growth team moves fast, and a lot of what we build is meant to be thrown away. Knowing which parts aren't is the real craft. We'd rather you weigh speed against quality, scale, and risk out loud, with reasons, than default to one end of it. Keep the standard where it counts Testing, observability and sensible security defaults aren't the opposite of speed on a surface this exposed. They're what makes speed survivable. When you ship something, you check that it works for real people in production. Use AI properly AI-native development is how this team works, and we want someone fluent in it who'll keep pushing the rest of us. You're still on the hook for what ships. Read it, test it, understand it, whoever or whatever wrote the first draft. Build for the people who use what you build Your users aren't only visitors to the site. They're marketers, copywriters, designers, localization teams, and other engineers. The questions worth asking include: how do we make publishing easier, automate the boring parts, improve the quality of what AI produces, take friction out of editing, and put experimentation in more hands? Good platforms disappear into the background. When this one works, everyone else gets faster. What success looks like Not lines of code. Business results, and how quickly we learn. More visitors turning into signups Faster experimentation Better discoverability across search engines and AI assistants A faster website Attribution we can trust Less manual work and quicker publishing A better experience for the engineers and editors who use the platform More leverage from automation and AI Who you are You live and