About the role
As an AI Developer at Digital Fans, you build AI-powered products and workflows that do real work for our clients. We work with companies to move beyond isolated AI experiments and build solutions that are integrated with their data, systems, brand context and existing ways of working. This can include everything from content and campaign automation to data analysis, internal tools and customer-facing assistants.
Your focus will be on turning ideas and use cases into working solutions. You will build LLM-powered features, agents and automated workflows, working closely with senior technical and product leadership as well as developers, designers and strategists.
Our core framework is Mastra and our main development language is TypeScript, but we care more about how you think about AI systems and how you turn emerging technology into useful, reliable solutions than which specific framework you have worked with before.
What you’ll do
Build LLM-powered features and agent workflows
Develop tools, memory, multi-step orchestration and human-in-the-loop flows
Integrate models from OpenAI, Anthropic, Google and other providers
Connect agents to client data sources, CRMs, content platforms and marketing tools
Build RAG pipelines and work with embeddings, retrieval and context
Develop integrations that connect AI capabilities with existing systems and workflows
Build product experiences around AI capabilities together with fullstack developers and designers
Develop evals, monitoring and feedback loops so AI behaviour can be measured and improved
Prototype new ideas quickly and turn successful concepts into robust production services
Continuously explore new capabilities across the fast-moving AI and agent ecosystem
Work closely with senior technical and product leadership to turn direction and priorities into working solutions
Share learnings and contribute to how the wider team builds with AI
Experience
2+ years of professional software development experience
Strong experience with TypeScript and Node.js
Hands-on experience building LLM-powered features or applications
Experience with prompt design, tool calling, structured outputs and streaming
Experience with a modern agent framework or SDK such as Mastra, OpenAI Agents SDK, Claude Agent SDK, LangGraph or Vercel AI SDK
Understanding of embeddings, vector stores, retrieval and RAG
Experience integrating applications with external data sources, APIs or platforms
Experience with Mastra, Amazon Bedrock AgentCore and cloud environments is a plus.
Who you are
You are a hands-on builder who enjoys turning ideas into working solutions
You are deeply curious about AI and follow how the technology and ecosystem are evolving
You start with real client and user problems rather than technology for its own sake, and enjoy applying new capabilities to real problems rather than demos
You have a strong software development foundation and care about turning AI into reliable products and workflows, balancing experimentation and speed with reliability, safety and maintainability
You are comfortable working in an area where the best approaches are still evolving
You learn quickly, move from prototyping to testing in real contexts, and ask for input when it helps you move forward
You enjoy working closely with people from different disciplines — developers, designers, strategists and project leads
You are comfortable working across multiple projects and ready to take increasing ownership as your experience and our AI capabilities grow
You are fluent in English, written and spoken
About Digital Fans
Digital Fans is a digital growth partner based in Stockholm. We work at the intersection of strategy, design, technology, data and AI to build digital products, platforms and solutions that create measurable growth and efficiency for well-known Nordic and international brands.
We are a small, senior team where developers work closely with designers, strategists and other specialists, with short decision paths and real influence over what we build. As part of NORD DDB, we combine the pace and collaboration of a smaller team with the reach of a larger network.