What you’ll do

• Build and maintain Python and SQL based systems for data pipelines, analyses, monitoring, and automated alerting

• Evolve Klarna's abilities to measure and monitor its business critical metrics from an AI-driven perspective

• Own projects end-to-end in time-boxed phases: scoping (1-2 weeks) → building → deploying → iterating

• Present technical work and tradeoffs to senior leadership

• Support and maintain what you build – no throwing projects over the wall

• Work publicly in Slack channels with radical transparency (all work visible to the team)

Who you are

• AI-First Engineer: Heavy hands-on experience with OpenAI/Anthropic APIs, prompt engineering, and AI-assisted coding tools (Cursor, GitHub Copilot, Claude Code, etc)

• Tech Stack Flexible: Comfortable working across Python, Docker, AWS, APIs, databases – you adapt to the problem, not the other way around       

• Business-Oriented: You translate stakeholder needs into technical solutions and care about why we're solving a problem, not just how            

• Iterative Shipper: You build MVPs in 1-2 week cycles, gather feedback, and iterate quickly                                                      

• Change Resilient: You thrive when priorities shift, requirements evolve, and ambiguity is the norm                                              

• Self-Driven: You proactively unblock yourself, drive projects forward, and communicate openly in public channels

 Awesome to have                                                                                                                                   

• Go coding language

• Good understanding of common design patterns and comfortable with modern Python 3 practices (type hints, protocols, Pydantic, uv)

• Experience with Terraform, Airflow, Slack API, OpenSearch, SPARQL, CI/CD

• Track record of maintaining production systems while building new features

• Background working with cross-functional stakeholders in product, analytics, and business operations                                                                   

• Comfort working in highly transparent, documentation-heavy environments                                                                         

• Experience killing or rescoping projects that aren't delivering value