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 breathe the web. You find it interesting how modern sites get built, found, measured and improved, and you like understanding the whole stack, from browser rendering and frontend architecture through to search engines, analytics, AI and experimentation. You care about the systems behind the experience as much as the experience itself, and you think in platforms rather than projects.

You're curious about users and customers, and comfortable having an opinion about what we should build, not only how to build it. The future of AI excites you, and so does the unglamorous engineering that makes AI useful in practice.

You share what you know. You write things down, you give people context, and the people around you get better for working with you.

You'll probably have experience with

React, Next.js, TypeScript, and modern frontend engineering

Technical SEO and modern search technologies

AI search, structured content and discoverability

Web analytics and event instrumentation

Server-side tracking and Conversion APIs

Marketing attribution and analytics

Experimentation platforms and A/B testing

Core Web Vitals and frontend performance

APIs, integrations and automation

Headless CMS platforms and component-driven architectures

AI-assisted software development

Modern deployment platforms such as Vercel

Building internal tooling and developer platforms

Nobody has all of this. Tell us which parts you'd be picking up along the way.

How we work, and who this suits

We're an outcome-oriented team. We work closely with Product, Design, Engineering, Marketing and Analytics to find opportunities, test ideas and build things that move the business. We'd rather be fast and learn than be perfect.

Two honest things about the team, because they're the difference between enjoying this job and not.

The website is everyone's front door, so plenty of work gets pushed at us from outsi