Full Stack Engineer

## About the Role As a Full Stack Engineer at Nooxit GmbH, you will be part of a remote-first team that is revolutionizing the finance industry with AI-powered automation solutions. Your day-to-day tasks will involve designing and building highly available, scalable cloud applications, developing new features and microservices, and ensuring the accuracy and reliability of AI models. You will work closely with the product, data science, and engineering teams to ship meaningful improvements and contribute to the company's engineering practices and tooling.

The role entails a deep understanding of AI models, their limitations, and their potential biases. You will be responsible for building observability infrastructure, designing evaluation pipelines, and defining key performance metrics to measure model accuracy. Your work will have a direct impact on the company's mission to automate finance processes and free finance teams from repetitive tasks.

Nooxit GmbH values diversity, inclusion, and creativity, and the team is composed of experts from various backgrounds, including consulting, venture building, autonomous driving, space technology, and cognitive science. As a Full Stack Engineer, you will have the opportunity to work with a talented team and contribute to the company's growth and success.

## What You Will Do - Design and build highly available, scalable cloud applications end-to-end - Develop new features and microservices within the existing infrastructure - Build and own observability infrastructure for AI systems, including accuracy dashboards, performance monitoring, anomaly detection, and alerting on prediction quality - Design and maintain evaluation pipelines that continuously measure model accuracy across document types, edge cases, and customer environments - Define and track key performance metrics, such as precision, recall, confidence thresholds, and drift indicators, and turn them into actionable engineering work - Instrument services with structured logging, tracing, and metrics collection to ensure full visibility into AI behavior in production - Improve and refactor existing services for performance, reliability, and maintainability - Write clean, testable, well-documented code and participate in thoughtful code reviews - Collaborate closely with product, data science, and fellow engineers to ship meaningful improvements - Contribute to engineering practices, tooling, and architecture decisions

## What We Are Looking For - Strong proficiency in Python and TypeScript - Solid experience with Docker, Git, and cloud-based development workflows - Familiarity with SQL databases, preferably PostgreSQL - Experience with or willingness to work with Pytest, CI/CD pipelines, Kubernetes, Terraform, and Helm - Comfort working across backend and frontend, with a willingness to learn and adapt - Experience with testing practices and a quality-first mindset - A genuine passion for AI accuracy and observability - Comfort with metrics and data analysis, thinking in terms of precision, recall, error rates, and confidence distributions - Proactive, communicative, and comfortable working autonomously in a remote team

## Nice to Have - Experience with machine learning frameworks and libraries - Knowledge of finance and accounting principles - Familiarity with agile development methodologies and version control systems - Experience with cloud-based platforms, such as AWS or Google Cloud

## Benefits and Perks - Competitive salary and benefits package - Opportunity to work with a talented and diverse team - Flexible working hours and remote work arrangements - Professional development and growth opportunities - Access to cutting-edge technologies and tools - Collaborative and dynamic work environment - Recognition and reward for outstanding performance

- Tip: Showcase your proficiency in Python, TypeScript, and cloud-native technologies by providing examples of personal projects or contributions to open-source repositories.

• Tip: Highlight your experience with AI models, machine learning frameworks, and data analysis, and be prepared to discuss your approach to model accuracy and observability.
• Tip: Emphasize your ability to work independently and collaboratively in a remote team, and demonstrate your communication skills through clear and concise writing samples.
• Tip: Prepare to discuss your experience with testing practices, quality-first mindset, and continuous integration and deployment pipelines.
• Tip: Research the company's mission, values, and products, and be prepared to ask informed questions during the interview process.
• Tip: Be prepared to provide examples of your problem-solving skills, creativity, and adaptability in a fast-paced and dynamic environment.