Revenue Operations Engineer

Mentimeter is an engagement company with a simple goal: to make every leader better. Through interaction, insights and recommendations, its platform helps organizations turn participation into better understanding and stronger performance.

Founded in Stockholm in 2012, Mentimeter is used by 20 million people each month across 1.3 million organizations. At Mentimeter, we believe better leadership starts with listening and that the strongest results are achieved together. That’s why we foster a culture built on curiosity, collaboration and shared ownership. By joining us, you’ll help leaders turn participation into deeper understanding and stronger performance, advancing our ambition to help more than one billion people listen, learn and work better together.

The role

We're building a Revenue Operations function where AI, automation and systems design are the core of how we scale. Not as a layer on top of how we work, but as the way we work: systems handle what can be systematised, so our reps spend their time on what only people can do, building relationships, reading a room, making the judgement call. This role sits at the centre of that.

It is a full-stack internal product role. Your users are our Enterprise GTM reps and leaders; your job is to understand how they work, find where friction or guesswork slows them down, and solve it with tailored, proactive solutions. That means designing how our revenue stack connects, embedding AI into live revenue workflows, and shaping the role-specific surfaces our teams work from. You own how it's architected, how it's automated, and how it evolves as the business does.

You’ll sit in the RevTech & Ops team within Revenue Operations, reporting to the RevTech & Operations Director, and work day-to-day with Sales, Marketing, CS and Analytics. You treat "can this be automated?" as the first question, not the last. You care as much about whether we're solving the right problem as about how it's solved, which means understanding how a sales person actually spends their day. And you'd rather ship a working v1 this week than a perfect design next quarter. You decide how things should be built, build a lot of it yourself, and leave behind architecture someone else can read and extend.

What you'll do

• Build internal tools. Design, build and maintain the role-specific UI our Enterprise reps and leaders work in every day. Connect it to the full revenue stack, iterate with the people using it, and keep it fast and reliable as the business changes.
• Remove manual work from GTM roles. Find the repetitive work in revenue teams and automate it with n8n, Clay, CRM automation and AI where it earns its place. Set the automation principles so what you build stays maintainable.
• Own the architecture. Keep the revenue toolstack (sales and marketing) healthy: data models, routing logic, account recycling, activity tracking, invoice objects and the automation between them. Fix what breaks, and design so it breaks less.
• Connect the systems. Build and maintain integrations across the stack via APIs so data moves cleanly and reliably.
• Guard the data. Set governance standards, ownership, definitions, structure, compliance, so reporting stays trustworthy as the stack grows.
• Shape what's next. Assess new tools and architectural changes and lead the complex ones: toolstack replacements, lifecycle redesigns, projects where the outcome is known but the path isn't.
• Work like a modern engineer / builder. Understand logic and dependencies. Use Cursor, Claude code, Vercel and GitHub to scale your own output.

What success looks like

The metric this role moves is ARR / Cost of GTM. In practice: reps spending their time in one place instead of six, fewer hours of manual work in GTM roles, fewer break-fixes, integrations that works, and data people trust without double-checking.

What you bring

• 3+ years in RevOps, Engineering, GTM systems or a similar role with real technical depth
• Hands-on experience with a CRM system (e.g. Salesforce, HubSpot): architecture, automation, objects, reporting
• A good understanding of APIs, webhooks, git and system integrations
• A current grasp of what agentic AI can and can't do today, and the curiosity to keep up
• High business understanding: you can tell a real problem from a loud one and prioritise accordingly
• Systems thinking: you care about clean architecture and long-term maintainability, not just getting it working
• A strong bias toward execution: proactive, action-oriented, builder's hat on by default

Strong candidates may also have

• An engineering background and/or built internal tools for operational teams
• Experience in a Sales or Marketin