Role Description We're looking for a Full Stack Engineer who wants to build things that matter — someone who's equally comfortable designing a clean API as they are shipping a polished frontend feature, and who genuinely cares about whether the AI behind it is actually getting things right. Our product makes critical financial decisions for enterprise customers, so accuracy isn't a nice-to-have — it's everything. We want someone who's obsessed with observability: if the AI extracts the wrong line item, misclassifies a transaction, or drifts in confidence over time, you want to know about it before anyone else does. You'll build the systems that measure, surface, and improve model performance — from evaluation pipelines and accuracy dashboards to real-time alerting on prediction quality. You'll work across the stack to develop, improve, and scale cloud-native applications while ensuring we always have a clear, data-driven picture of how our AI is performing in the wild. You'll have real ownership, creative freedom, and the opportunity to shape both the product and the engineering culture as we grow. Qualifications - Strong proficiency in Python and TypeScript - Solid experience with Docker, Git, and cloud-based development workflows - Familiarity with SQL databases (PostgreSQL preferred) - Experience with or willingness to work with: Pytest, CI/CD pipelines, Kubernetes, Terraform, Helm - Comfort working across backend and frontend — you don't need to be an expert in both, but you're curious and willing to learn - Experience with testing practices and a quality-first mindset - A genuine passion for AI accuracy and observability - Comfort with metrics and data analysis - Proactive, communicative, and comfortable working autonomously in a remote team - Be able to work within 2 hours +/- of the European timezone Requirements - Previous experience in a startup or fast-moving environment - Hands-on experience building evaluation pipelines, accuracy benchmarks, or monitoring for ML/AI systems in production - Experience with observability tools and practices (e.g., Prometheus, Grafana, Datadog, OpenTelemetry, structured logging, distributed tracing) - Familiarity with ML metrics concepts — confusion matrices, F1 scores, calibration curves, data drift detection, A/B testing - Experience working at the intersection of engineering and data science, helping translate model quality into measurable product outcomes - Interest in AI/ML applications or fintech - Experience mentoring other engineers or helping shape engineering processes Benefits - Fully remote — work from anywhere in the world - Flexible working hours — we care about output, not clocked hours - Competitive salary with room to grow as the company scales - An open, diverse, and international team that values collaboration and curiosity - The chance to work with renowned enterprise customers and help build what could become the next finance automation category leader - Real ownership and influence over the product and engineering direction Company Description Nooxit is building the next generation of AI-based finance process automation tools for medium and large enterprises. We are putting accounting on autopilot. Our software leverages modern Deep Learning and NLP technology to liberate finance teams from repetitive document capturing, manual compliance reporting, and tedious accounting tasks. This helps our customer's finance team to save time and money, prevent fraud, and be globally compliant with local financial regulations. Our remote-first company was founded in 2019 and is investor-backed. Our diverse team has previous backgrounds in Consulting, Venture Building, Autonomous Driving, Space Technology, and Cognitive Science. Our customers are international medium and large companies from different sectors (for example ZF Friedrichshafen). We are headquartered in Berlin with additional office space in the Cologne area.