Our requirements
What you bring
▪️A degree in computer science, software engineering, data science or a related field, or equivalent practical experience
▪️ 5+ years of professional software engineering, including 2+ years building LLM-based solutions that run in production
▪️Hands-on experience with agents, tool calling, retrieval and evaluation of LLM systems
▪️ Experience extracting structured data from documents, drawings, images or emails is a strong advantage
▪️ Experience integrating AI with enterprise systems such as ERP or CRM; SAP is an advantage
▪️ Experience with data platforms such as Snowflake, Databricks or Microsoft Fabric is an advantage
▪️ Experience with process automation or RPA is a plus
Technical skills
▪️Strong Python, plus solid skills in APIs, databases, Git and automated testing
▪️ LLM APIs, agent frameworks and protocols such as MCP
▪️ Evaluation and observability tooling, prompt versioning, guardrails and cost tracking
▪️ Cloud platforms, e.g. Azure, with CI/CD and infrastructure as code, e.g. Terraform
▪️AI coding agents and AI-assisted code review
▪️ Fluent English
As a person
▪️ Hands-on and pragmatic, focused on value rather than features
▪️ Comfortable saying no to nice-to-haves
▪️Curious and quick to learn as the technology moves
▪️ A team player who shares knowledge and takes ownership of what runs in production
Your responsibilities
Keep our new digital products running well
▪️Maintain, monitor and stabilise our new digital products in production for Denmark and Sweden
▪️ Find root causes and fix issues quickly, together with sales support and the rest of the team
▪️ Keep the solution secure, documented and easy for others to work on
Build only what is needed
▪️Develop the features that clearly move our KPIs, and challenge requests that are only nice to have
▪️ Work from a prioritised backlog together with the team and the Product Leader
▪️ Ship small, frequent improvements and measure their effect
Measure and improve AI quality
▪️ Build evaluation sets and automated tests that show whether a change really improves results, e.g. automation rate and quote accuracy
▪️ Improve prompts, context, retrieval and tools based on evidence, not guesswork
▪️ Track latency, token usage and cost, and optimise where it matters
Build new digital products
▪️ Help build our new digital product once the design is set, including the shared rules, pricing, validation and quoting capabilities
▪️ Build agents, services and MCP servers that connect to ERP, CRM and product data
▪️ Follow the target architecture and patterns set together with the AI Architect
Engineer with quality at speed
▪️ Use AI coding tools and AI-assisted code review to deliver fast without cutting corners
▪️ Write clean, tested code with CI/CD, infrastructure as code and good observability
▪️ Review code with your colleagues and share knowledge across the team
Choose the right tool
▪️ Use AI where it adds value, and deterministic rules, integration or conventional code where they are more reliable
▪️ Combine LLM-driven and deterministic logic safely, with guardrails and human review where needed
▪️Bring ideas, prototypes and honest feedback to the AI Architect and Product Leader