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Founding Fullstack Engineer (gn) @ Pre-Seed AI-Native Enterprise Platform, Helsinki

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Job Description

This is an Atlantic Labs portfolio venture. Find out more about us and other opportunities in our portfolio here.

About the Venture

We're a stealth venture building an AI-native platform for enterprise business modelling and scenario planning. At its core is a graph-based modelling engine combined with an intuitive grid UI and an AI co-pilot that accelerates model creation and improves decision quality.

Our goal is to replace Excel as the default for complex business models, while offering a more flexible and easier alternative to current heavyweight enterprise tools. It's a new kind of tool for business controllers and FP&A leaders.

We're a founding team of three with deep expertise in enterprise software, data modelling, and product execution. Backed by pre-seed financing, we're working closely with design partners in the upper mid-market and enterprise space, and preparing to launch soon.

We’re establishing our HQ in Helsinki and would be excited to hear from you who are already based here or open to relocating. That said, we are open to hybrid arrangements within a reasonable aligned timezone.

About the Role

Weʼre looking for a Founding Full Stack Engineer to join us at the earliest stage, helping to design, build, and scale the product from the ground up. This is a hands-on role where youʼll move fluidly between backend, frontend, and integration work, depending on whatʼs needed to get us from idea to production.

You might lean more toward backend (e.g. building our graph-based modelling engine, APIs, event-driven infrastructure) or frontend (e.g. creating an intuitive grid/graph UI, collaborating with design to make complex modelling simple), but youʼll need to understand and contribute across the stack.

More specifically you will

  • Build core product features end-to-end, from database to API to frontend UI
  • Help design and develop our scalable modelling engine combining graph and grid systems
  • Integrate AI/LLM capabilities into user-facing workflows
  • Contribute to architecture decisions that balance rapid iteration with enterprise-grade security, performance, and maintainability
  • Work closely with founders and customers to shape the product direction
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