Product Engineer, 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.

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.

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.

Frontend architecture, the component library, deployment pipeline, performance, and the foundations everything else sits on.

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.

Technical SEO, structured data, AI search, and whatever comes next for being found, both by search engines and by AI assistants.

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.

The infrastructure behind fast experiments, personalization, feature flags and continuous optimization, and making that infrastructure usable by people who don't write code.

Tooling, automation and AI-assisted workflows that make life easier for marketers, designers, copywriters, editors and localization teams.

Working with Design on a component system that scales, stays consistent and accessible, and doesn't slow anyone down.

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.

We call this a Product Engineer role, and we mean something specific…