The Role

The Nordics is one of the most exciting European markets for Gigs. With world-class fintech infrastructure, highly digitised economies, strong telecom ecosystems, and some of Europe’s most sophisticated B2B buyers, the region is a natural fit for what we’re building.

We’re looking for a Go to Market (GTM) Lead to own our Nordics strategy and execution end-to-end - from landing lighthouse customers and building operator partnerships to setting up and growing a high-performance regional team.

You’ll work closely with our VP of Growth and global leadership to establish Gigs’ presence across Sweden, Denmark, Norway, and Finland. This is a founding market role - a consultative, long-cycle deal-maker's job: you'll be convincing sophisticated fintechs and enterprises to embed an entirely new business line. High ownership, direct founder visibility, and a real mandate to build.

If you thrive in zero-to-one environments, have a strong network across the Nordic fintech, telecom, and technology landscape, and know how to pair sharp strategy with relentless execution - this role is for you.

What You’ll Do

• Own the Nordics market strategy: Define and execute Gigs’ go-to-market approach across Sweden, Denmark, Norway, and Finland, in close collaboration with global leadership.
• Drive commercial growth: Identify, negotiate, and close high-value partnerships with fintechs, and enterprise customers across the region.
• Build Gigs’ Nordics presence: Represent Gigs at key industry events, build your personal profile, and establish Gigs as a serious player in the Nordic ecosystem.
• Build and lead a team: Recruit and develop a lean, high-performance local team as the market scales.
• Connect the dots: Act as the bridge between Nordic market realities and Gigs’ global product, engineering, and leadership teams — channelling the right market insight to shape our roadmap.

What We Are Looking For

• Proven track record of launching or scaling a market or business line in the Nordics — ideally in fintech, payments, SaaS, telecom, or marketplace businesses.
• Strong commercial instincts: you can close deals, build partnerships, and spot high-value opportunities before they’re obvious.
• Deep network and credibility across the Nordic fintech and technology ecosystem — particularly in Sweden, Denmark, and Finland.
• Solid understanding of the Nordic regulatory landscape and business culture across the region’s four markets.
• Excellent communicator and relationship builder, internally and externally, across cultures and seniority levels.
• Self-starter: comfortable with high ownership, ambiguity, and fast-moving environments - you'll be writing the playbook, not inheriting one.
• AI-curious and practically so: you've meaningfully changed how you work using AI tools and agents, and you're energised by what that unlocks for a lean, high-output team.
• Fluency in English required; a Nordic language(s) is a strong plus.

Applications for this role will be reviewed in w/c 11th May 2026. We will be in touch with all candidates after that date.

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Mission 

As a Sr Specialist Solutions Architect (SSA) - ML & AI Engineer, you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide enterprise and strategic customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader.

The impact you will have:

• Architect production level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.  
• Serve as trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems
• Build, scale, and optimize customer AI workloads and apply best in class MLOps to productionize these workloads across a variety of domains
• Provide advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks
• Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks’ AI offerings

What we look for:

• 7+ years of hands-on industry ML experience in at least one of the following:
• ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
• AI Engineer: Experience with the latest techniques in LLMs & agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
• Experience with data engineering, or a good understanding of the concept of data engineering
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through ML & AI
• [Preferred] 5+ years customer-facing experience in a pre-sales or post-sales role
• Can meet expectations for technical training and role-specific outcomes within 3 months of hire
• This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed

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