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.

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.

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.

Internal

platform​

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 by it.

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.

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.

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.

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.

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.

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

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.

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 outside. There's more ad hoc work and more context switching here than on a core product team. Some engineers

love that and some find it draining. Both are reasonable, and it's worth knowing which one you are before you apply.

Some

of the most valuable work also takes months to show up in a graph. SEO, measurement, platform foundations. You need to invest in

what you believe in before the numbers move, and be honest enough to stop when the evidence says you got it wrong.

You'll help shape one of the world's leading product-led growth companies

while it goes through a real transformation. Modern web technology, AI-native ways of working, and a small team that likes

curiosity, experimentation, and good craft.

And you'll build the operating system behind how millions of people discover

Mentimeter.

At Mentimeter, we believe in fair and transparent compensation that grows with you.

The salary range for this role is SEK 54,000–SEK 70,000 per month. It’s intentionally broad to reflect the different stages of

growth within the role: from early development to deep expertise and meaningful impact.

Where an individual is

placed within the range depends on factors such as relevant experience, demonstrated skills, and alignment with the role’s

requirements. We’re committed to supporting your growth. You’ll have ongoing development conversations with your manager, and your

salary will evolve as you build skills and contribute to our mission.

In addition to your monthly salary,

we offer a comprehensive benefits package—learn more about it here:

​https://www.mentimeter.com/benefits/stockholm.​

What Mentimeter can offer

​At Mentimeter we can offer a diverse and inclusive

work environment supported by smart and driven colleagues. We believe in continuous professional development for all of our

colleagues and therefore offer access to a leadership program (including external personal coach) and relevant education to ensure

that we continue to be state-of-the-art when it comes to innovating and building Mentimeter. Your place will be in a growing

company with lots of career opportunities, working on a beloved product used by more than 300 million people. It’s not all about

work though, we also offer a very healthy view on work-life balance.

All of this comes attached with a competitive

compensation and benefits package, including pension contributions. Learn more about our benefits by visiting our Benefits & Perks page

AI and Hiring at Mentimeter​

At Mentimeter, we believe AI helps us work smarter - but it

never replaces the human assessment, curiosity, and personal connection that define our culture and our hiring. We use AI as a

sparring partner: to bounce ideas, bring new perspectives, support structure, and make our work more efficient. But the meaning,

decisions, and interactions always come from people.

AI does not screen or decide on candidates.

There is no automated filtering, ranking, or decision-making in our recruitment process. Every

application is reviewed by a person.

Hiring teams may use AI to

support their work - for example, to structure notes, prepare interview questions, or organize their thinking.

AI strengthens our work, but it does not define it. At Mentimeter, we’re not building an AI-driven

hiring process - we’re building a people-first culture, where technology helps us listen, learn, and grow together.

Culture at Mentimeter

​At Mentimeter we believe in giving everyone a voice - regardless of who you are. So

we build a platform that does just that. Our platform is not only our product but also our organization. A platform where people

feel safe, where differences are embraced, a place where you can have fun. We strongly encourage applicants who are people of

color, LGBTQ+, women, people with disabilities, and/or formerly incarcerated people, and a college degree is not strictly

required. In order to give everyone a voice, we need to be as diverse as our users.

Learn more about our culture by

visiting our Culture page.

Review our Privacy Policy for more information.