Nooxit is building the next generation of AI-powered finance process automation for medium and large enterprises. We're putting accounting on autopilot.
Our software uses modern deep learning and NLP to free finance teams from repetitive document capturing, manual compliance reporting, and tedious accounting tasks — helping them save time, prevent fraud, and stay compliant with local financial regulations across the globe.
Founded in 2019 and investor-backed, we're a remote-first company headquartered in Berlin with additional space in the Cologne area. Our customers include international mid-market and enterprise companies across sectors.
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. Build and own observability infrastructure for our AI systems — accuracy dashboards, performance monitoring, anomaly detection, and alerting on prediction quality
Collaborate closely with product, data science, and fellow engineers to ship meaningful improvements
Strong proficiency in Python and TypeScript
Familiarity with SQL databases (PostgreSQL preferred)
Comfort working across backend and frontend — you don't need to be an expert in both, but you're curious and willing to learn
A genuine passion for AI accuracy and observability — you're the kind of person who wants to understand why a model got something wrong, builds a dashboard to track it, and sets up an alert so it doesn't happen silently again
Comfort with metrics and data analysis — you think in terms of precision, recall, error rates, and confidence distributions, not just "it seems to work
Proactive, communicative, and comfortable working autonomously in a remote team
Bonus Points
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
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
Benefits
Fully remote — work from anywhere in the world
Competitive salary with room to grow as the company scales
An open, diverse, and international team that values collaboration and curiosity
If you have a GitHub profile or portfolio, feel free to include it.