The role

Mentimeter is looking for a Product Engineer to join our Payments team and help shape how customers pay for and manage their subscriptions.

The Payments team owns the checkout experience, billing systems, subscription lifecycle, and integrations with payment providers like Stripe. We work on reducing friction in critical customer journeys - from initial signup through renewal and cancellation. We're also thinking bigger: exploring more flexible billing models, improving how we handle invoicing and financial reporting, and building the infrastructure to support Mentimeter's growth.

The technical landscape is distributed systems, event-driven architecture, and complex integrations. We partner closely with Product, Finance, Sales, and Support to balance customer experience with business requirements. This is a team that works together -pairing, mobbing, and bringing diverse perspectives to problems that matter.

You'll have a genuine chance to influence Mentimeter's payments strategy and help define how hundreds of thousands of customers experience billing at our platform.

The Team

The Payments team is part of our Capabilities area, which builds critical platform experiences. We're a close-knit group: a product manager, an engineering manager, and backend-focused engineers who care about getting the details right. We work across the entire stack, but most of our work is backend, distributed systems, integrations, and data pipelines.

We're collaborative by nature. We discuss big decisions openly, challenge ideas respectfully, and support each other. We're not a ticket-pushing team. We own outcomes, think about trade-offs, and take initiative to improve what we've built. We're also learning together - experimenting with AI adoption, refining how we work, and building skills we didn't have yesterday.

What you'll do

• Design, build, and improve payment and billing experiences that reduce friction and delight customers
• Work on subscription lifecycle systems, pricing logic, and invoicing pipelines
• Integrate and maintain relationships with payment providers - understanding their APIs, limitations, and cost models
• Build systems that handle distributed transactions reliably, with observability and fault tolerance
• Collaborate across teams - understanding what Finance needs, what Sales is selling, what Support is hearing from customers
• Think about how we evolve our billing capabilities - moving beyond our current patterns to support new pricing models and business requirements
• Take initiative on projects that improve our systems, domain knowledge, or team practices
• Stay curious about payments, distributed systems, and AI adoption in software development

Who you are

You're comfortable working across the backend stack and think in terms of systems and trade-offs. You have real experience shipping backend services to production - you understand latency, observability, and knowing what to test.

You're curious by nature. You ask good questions, learn quickly, and aren't intimidated by domains you haven't worked in before. You have opinions, you share them respectfully, and you're willing to be challenged in return.

You think about outcomes, not tasks. You can take a fuzzy problem, break it down, and drive it to completion. You work well with others - you enjoy pairing, you communicate clearly, and you can represent the team in cross-functional conversations.

This is a full-stack product engineering role with a heavy emphasis on the backend. The primary responsibilities will involve backend development in Ruby. 

The successful candidate will also contribute to and own frontend features. This is a perfect fit for an engineer who is passionate about scalable systems and comfortable working across the entire tech stack, while maintaining a main focus on backend architecture.

It's a big plus if you have

• Experience with payments, billing, subscriptions, or Stripe - you understand the domain and its quirks
• Experience building systems that integrate with external APIs and handle eventual consistency
• Familiarity with distributed systems thinking - understanding event-driven architecture, idempotency, and failure modes
• Some infrastructure or platform thinking - you've thought about observability, monitoring, and operational excellence
• Experience working on products with internal stakeholders - Finance, Sales, Support - and understanding their needs
• Comfort pairing, mobbing, or working in collaborative code sessions
• Interest in AI adoption and how AI tools can improve our development process

It's okay if you don't have

• Specific experience with payments or Stripe (domain knowledge is learnable)
• Deep infrastructure expertise (curiosity and willingness to learn matter more)
• Ruby experience (we value engineers who are problem solvers and have a growth mindset)

How we work with AI
We're actively building AI into how we build software - and as part of the product itself. Every engineer has access to tools like Cursor, Claude, and Codex, and we encourage you to use them to pair on tricky problems, explore unfamiliar codebases and to prototype and experiment. We're not prescriptive about how we use them, but we are curious about what works and what comes next in how products get built. Our teams regularly share workflows, and lessons learned, and we treat AI adoption and fluency as a skill we're all developing together - both in how we build and in what we build for our customers.

The role

Mentimeter is looking for a Product Engineer to join our Identity team and help shape how users and organizations authenticate, access, and manage their presence across our products.

The Identity team owns the enterprise-grade identity surface of Mentimeter: SSO and SAML authentication, SCIM-based user provisioning, domain control, and email verification among others. Our mission is to create intuitive, scalable solutions for identity management of users and participants - lowering the threshold for enterprises to start adopting our enterprise offering with minimal support. That means everything from a first-time user signing in seamlessly, to enabling organisations of tens of thousands to onboard into their workspace smoothly through automated provisioning and access management.

Beyond our own systems, we act as an enabling function for other teams - advising on standardized authentication practices across Mentimeter’s products, and ensuring that both internal and external integrations follow consistent, secure patterns.

The technical landscape spans distributed systems, security-sensitive flows, and deep integrations with identity providers. We partner closely with Product, Security, Sales, and Support to balance user experience with enterprise requirements. 

This is a team that works together - bringing diverse perspectives to problems that matter. You’ll have a genuine chance to influence Mentimeter’s identity strategy and help define how millions of users and their organizations experience authentication through our products.

The team

The Identity team is part of our Capabilities area, which builds critical platform experiences. We’re a close-knit group: a product manager, an engineering manager, and engineers who care deeply about getting security and user experience right at the same time. We work across the entire stack, but most of our work is primarily in the backend. We’re collaborative by nature. We discuss big decisions openly, challenge ideas respectfully, and support each other. 

We’re not a ticket-pushing team. We own outcomes, think about trade-offs, and take initiative to improve what we’ve built. We’re also learning together - experimenting with AI adoption, refining how we work, and building skills we didn’t have yesterday.

What you'll do

• Design, build, and improve authentication and identity experiences that are seamless for individual users and robust for large enterprises
• Work on SSO and SAML integrations, SCIM-based provisioning, domain control, email verification, and password authentication flows
• Integrate and maintain relationships with identity providers - understanding their protocols, limitations, and security models
• Build systems that handle security-sensitive flows reliably, with observability, auditability, and fault tolerance
• Enable other engineering teams by establishing standardised authentication practices and advising on identity patterns for new products and integrations
• Collaborate across teams - understanding what Security needs, what Sales is selling to enterprise customers, and what Support is hearing from organisations
• Think about how we evolve our identity capabilities - moving beyond current patterns to support new authentication methods, multi-product identity, and growing enterprise requirements
• Take initiative on projects that improve our systems, domain knowledge, or team practices
• Stay curious about identity, security, distributed systems, and AI adoption in software development

Who you are

You’re comfortable working across the backend stack and think in terms of systems and trade-offs. You have real experience shipping backend services to production - you understand latency, observability, and knowing what and when to test functionality.

You’re curious by nature. You ask good questions, learn quickly, and aren’t intimidated by domains you haven’t worked in before. You have opinions, you share them respectfully, and you’re willing to be challenged in return.

You think about outcomes, not tasks. You can take a fuzzy problem, break it down, and drive it to completion. You work well with others - you enjoy pairing, you communicate clearly, and you can represent the team in cross-functional conversations.

This is a full-stack product engineering role with a heavy emphasis on the backend. The primary responsibilities will involve backend development in Ruby. 

The successful candidate will also contribute to and own frontend features. This is a perfect fit for an engineer who is passionate about scalable systems and comfortable working across the entire tech stack, while maintaining a main focus on backend architecture.

It's a big plus if you have

• Experience with authentication, identity management, SSO, or protocols like SAML, OIDC, and OAuth - you understand the domain and its quirks
• Experience building systems that integrate with external identity providers and handle security-sensitive flows
• Familiarity with distributed systems thinking - understanding event-driven architecture, idempotency, and failure modes
• Some infrastructure or platform thinking - you’ve thought about observability, monitoring, and operational excellence
• Experience working on products with both end users and internal stakeholders - Security, Sales, Support - and understanding their needs
• Experience enabling other teams - advising on best practices, reviewing integration designs, or maintaining shared libraries
• Comfort pairing, mobbing, or working in collaborative environments
• Interest in AI adoption and how AI tools can improve our development process

It's okay if you don't have

• Specific experience with authentication or identity protocols (domain knowledge is learnable)
• Deep infrastructure expertise (curiosity and willingness to learn matter more)
• Ruby experience (we value engineers who are problem solvers and have a growth mindset)

How we work with AI
We're actively building AI into how we build software - and as part of the product itself. Every engineer has access to tools like Cursor, Claude, and Codex, and we encourage you to use them to pair on tricky problems, explore unfamiliar codebases and to prototype and experiment. We're not prescriptive about how we use them, but we are curious about what works and what comes next in how products get built. Our teams regularly share workflows, and lessons learned, and we treat AI adoption and fluency as a skill we're all developing together - both in how we build and in what we build for our customers.

The role

Mentimeter is looking for a Product / AI Engineer to join our Recommendation Engine team and play a key role in shaping how AI creates value across our product.

We have multiple AI-powered features live in production, including a multi-agent system serving real users at scale. The work spans LLM orchestration, structured output generation, chained analysis pipelines, prompt engineering, and evaluation. Going forward, the technical challenges deepen: richer context management across sessions, more sophisticated agent architectures, personalization and relevance at scale, and the extension of AI capabilities across the broader Mentimeter product.

Over 300 million people have used Mentimeter to run interactive sessions - gathering input, running polls, and collecting feedback. We're building the AI-powered system that helps users get more value from those interactions: understanding what they learned, deciding what to do next, and acting on it.

You'll have a genuine chance to influence Mentimeter's medium- and long-term AI strategy.

The team

The Recommendation Engine team builds AI-powered recommendations that help Mentimeter users turn what they learn into what they do next - not just once, but across sessions and over time. The system gets smarter as it accumulates context: user goals, past interactions, and what's worked before. The ambition is to support users through ongoing processes, not just individual moments.

Together with our sister team, Results, we form the Insights area, where AI is a core part of how we build product experiences. We're a full product team: a product manager, a product designer, an engineering manager, and engineers. We work closely and partner up with other product teams across Mentimeter, but we also own end-to-end user experiences in our own right.

The work shifts between modes - running experiments to learn what creates value, and building the features, systems, and experiences that deliver it. If you enjoy shaping product direction as much as writing code, and can move between exploration and execution, you'll fit in here.

What you'll do

• Design, build, and improve LLM-powered features that create real value for users
• Work on multi-agent architectures, orchestration, and context management in the service of real user goals
• Build evaluation and quality systems for AI features
• Make model selection, cost, and latency trade-offs for production AI systems
• Leverage user interaction data to inform and improve AI-powered features - from exploratory analysis to production pipelines
• Explore emerging AI capabilities and assess where they add real value versus where simpler solutions win
• Act as a central figure of applied AI expertise within the team and the broader engineering organization
• Stay current with a fast-moving field and bring what you learn back to the team

Who you are

You have genuine enthusiasm for building AI-driven products and have shipped LLM-powered work into live environments, where user behavior, cost, latency, and failure modes were part of the job. Your background might be in software engineering, data science, ML engineering, or something else entirely – what matters is that you combine solid judgment on LLMs and data with a product-centric approach and ship product experiences that users value.

You’re comfortable navigating uncertainty in a rapidly developing space, and you have a track record of tackling complex technical challenges. We’re especially interested in LLM work that reached production or sustained real use – commercial products, internal platforms with serious adoption, or open-source with a clear quality bar – and we’re open to other paths if you can show depth (what you owned, how you measured quality, what failed in the wild).

You think about what to build as well as how to build it. You communicate clearly, simplify complex technical concepts, and share ownership of outcomes with the rest of the team. You're comfortable working across team boundaries - liaising with other product teams, thinking about broader architectural needs, and representing AI expertise in cross-team discussions.

We don’t optimize for a specific number of years on a CV – careers aren’t linear. What we do need is seniority in the type and depth of experience. With that said, this is not an entry-level role – we’re hiring someone who can contribute at a senior level from early on.

It's a big plus if you have

• Experience with LLMs in production at scale - real traffic, real cost constraints, real failure modes, not just prototypes or side projects
• Experience building AI features where evaluation was a genuine challenge - designing evals for non-deterministic outputs, understanding where your system fails, measuring quality over time
• Experience working on a user-facing SaaS product - you understand subscription dynamics, product-led growth, and what it means to ship to paying customers
• An NLP or text analysis or applied data science background - the team works heavily with text: session responses, generated insights, structured recommendations
• Experience working across multiple languages or parts of the stack - the work here spans Python, Ruby, and TypeScript, and we value people who are comfortable learning what they don't already know

Not required

Swedish is not required - daily work is carried out in English, and the Mentimeter team currently boasts over 50 nationalities. A college degree is not strictly required.

Practical information

This is a hybrid/on-site role at Mentimeter HQ in Stockholm, where we expect you to be in the office at least 3 days/week.
Please note that we do not offer relocation sponsorship for the position.

Recruitment process

1. Introduction call
2. Culture interview, onsite if possible
3. Technical competence interview - a technical system design case with other engineers, onsite

Modern data platforms are built on events - well-defined, trustworthy signals that describe how users interact with products and systems over time. As a Data Engineer you will help build and improve the data platform that powers analytics, growth, personalization and decision-making across the company.

This role is part of the Data Platform team, where we design and maintain the core data infrastructure that serves Product, Marketing, Growth, and Analytics. You will focus on the systems and infrastructure that supports transforming batch and streaming data into high-quality datasets that downstream systems - from warehouses to activation tools - can rely on.

We are currently in the early stages of building out a new event-driven architecture, and this role will be part of shaping it. That means owning parts of the streaming infrastructure, contributing to foundational decisions about how events are structured and evolved, and having real influence over how data flows across the company for years to come.

This is a hybrid/onsite role located in Stockholm, our guideline is to spend 3 days a week at our office.

What you’ll do

• Design and operate data infrastructure (streaming and batch) and the systems that move data reliably at scale.
• Contribute to how events are defined, structured, and evolved across the platform.
• Ensure data quality, consistency, and observability across event pipelines.
• Ensure GDPR and PII compliance across data flows at scale.
• Contribute to data and architecture best practices that may span across the whole organisation.

Who you are

• A few years of experience as a Data Engineer or data-heavy backend engineer.
• Solid programming and data skills (e.g. SQL, Python, and/or JVM-based languages).
• Experience building and maintaining data pipelines in a modern cloud data stack.
• Experience managing infrastructure as code (e.g. Terraform or similar).
• A good understanding of data quality, observability, and reliability.
• Clear written communication skills in English and comfort working cross-functionally.
• Experience with streaming systems or near real-time data infrastructure (e.g. Kafka, Flink, or similar).

📍 Location: 

This is a hybrid/on-site role at Mentimeter HQ in Stockholm, where we expect you to be in the office at least 3 days/week.
Please note that we do not offer relocation sponsorship for the position.  

Not Required:

You don’t have to know Swedish (daily work is carried out in English and the Mentimeter team currently boasts over 50 nationalities!)

Modern data platforms are built on events. Not just logs or tracking points, but well-defined, trustworthy signals that describe how users interact with products and systems over time. As a Data Engineer with an Event background, you will help build and evolve the event-driven foundations that power analytics, growth, personalization, and decision-making across the company.

This role is part of the Data Platform team, where we design and maintain the core data infrastructure that serves Product, Marketing, Growth, and Analytics. You will focus on capturing canonical domain events and transform them to high-quality datasets that downstream systems — from warehouses to activation tools — can rely on with confidence.

The Data Engineering Team

The Data Engineering team builds and owns the data platform that enables the organization to understand its users and its business. We work closely with Product Engineering, Growth, Marketing, and Analytics to ensure that data is reliable, observable, compliant, and fit for purpose.

Within the team, this role brings deep expertise in event-based data modeling and martech-adjacent systems, strengthening Mentimeter’s ability to reason about user behavior, lifecycle metrics, and cause-and-effect across touchpoints. Your work will directly influence how events are defined, ingested, validated, and activated throughout the data ecosystem.

What you’ll do

• Model event data in the warehouse to support analytics, growth metrics, and lifecycle analysis.
• Ensure data quality, consistency, and observability across event pipelines.
• Collaborate with marketing and growth teams to enable reliable activation and personalization through tools such as Braze.
• Ensure GDPR and PII understanding and compliance across data flows, including consent handling and secure storage.
• Contribute to architectural decisions and best practices within the Data Engineering team.
• Act as the technical owner for Braze, including:
  • Defining and maintaining the event and user attribute contracts that power messaging, journeys, and personalization.
  • Ensuring data correctness, timeliness, and consistency between the warehouse and Braze.
  • Partnering with Marketing and Growth to enable safe, scalable activation patterns.

We believe you have

• Several years of experience as a Data Engineer, Analytics Engineer, or data-heavy backend engineer.
• Strong experience working with event-driven data models and behavioral data.
• Hands-on experience with event ingestion platforms (Segment or similar).
• Solid programming and data skills (e.g. SQL, Python, and/or JVM-based languages).
• Experience building and maintaining data pipelines in a modern cloud data stack.
• A strong understanding of data quality, observability, and reliability.
• The ability to understand and explain cause and effect in marketing and product data.
• Clear written communication skills in English and comfort working cross-functionally.

It’s a big plus if you have

• Experience working closely with martech platforms such as Braze.
• Previous experience as a Growth Engineer or in growth-focused product teams.
• Experience with streaming or near real-time data systems.
• Familiarity with user lifecycle frameworks and activation metrics.
• Experience working with GDPR-sensitive datasets at scale.

Not required

You don’t have to know Swedish (daily work is carried out in English and the Mentimeter team currently boasts over 50 nationalities!)

📍 Location: This is a hybrid/on-site role at Mentimeter HQ in Stockholm, where we expect you to be in the office at least 3 days/week.

Please note that we do not offer relocation sponsorship for the position.