AI Augmented Software Engineer [gn] Data Intelligence Platform

Jobgether · Germanymid

In short

▸Ingeniero full-stack que construye plataformas de inteligencia de datos con ayuda de IA.
▸Día a día: diseñar, codificar, desplegar y mantener funciones de backend y frontend, usando asistentes de IA como Claude Code o Cursor.
▸Lo destacado: se valora el uso deliberado de IA para aumentar la productividad, pero siempre con juicio humano al centro.

Fluent English required for collaboration and documentation.

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What they ask for

✓Experiencia probada como ingeniero full-stack en entornos SaaS.
✓Uso práctico de asistentes de codificación con IA (Claude Code, Cursor, similares).
✓Juicio técnico sólido para evaluar y mejorar soluciones generadas por IA.
✓Experiencia práctica con Scala o Java (backend) y TypeScript y Angular (frontend).
✓Conocimientos en arquitectura SaaS y fundamentos en AWS.
✓Mindset ágil con enfoque en iteración rápida, feedback y mejora continua.

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ScalaJavaTypeScriptAngularAWSDockerKubernetesGitHubCI/CDClaude Code

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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI Augmented Software Engineer [gn] Data Intelligence Platform based in Germany. This is an opportunity for a full-stack engineer to help build a modern data intelligence platform that enables organisations to discover, govern, and trust their data. You’ll work end-to-end across backend services and frontend experiences, taking features from initial concept through production delivery. AI coding assistants will be a core part of your engineering toolkit, helping you accelerate development while keeping human judgment at the center of technical decisions. You’ll contribute to scalable SaaS products where correctness, security, performance, and maintainability are critical. The role offers significant autonomy, encouraging you to identify problems, shape solutions, and move initiatives forward without waiting for detailed instructions. You’ll collaborate closely with product managers and engineers in an agile, feedback-driven environment focused on continuous improvement. It’s an ideal setting for a pragmatic builder who wants to multiply their engineering impact through thoughtful use of AI. Accountabilities Design and implement full-stack product features across backend services and frontend interfaces, ensuring strong performance, reliability, security, and maintainability. Take ownership of features from understanding requirements and technical design through implementation, testing, deployment, and production support. Use AI coding assistants such as Claude Code, Cursor, and comparable tools deliberately to accelerate development, reduce repetitive work, explore solutions, improve test coverage, and increase engineering leverage. Apply sound engineering judgment when using AI-generated output, reviewing, validating, and improving solutions rather than relying on automation without oversight. Participate actively in technical design discussions and code reviews, promoting clean architecture, secure development practices, and testable code. Troubleshoot production issues and participate in incident response, taking shared responsibility for the stability and reliability of the platform. Work closely with Product Managers to understand customer and business requirements early and translate them into clear, achievable technical solutions. Share technical knowledge with colleagues through documentation, technical sessions, and internal development practices. Help establish and improve AI-assisted engineering practices, contributing reusable approaches, workflows, and lessons learned across the team. Contribute to an agile working environment based on short feedback loops, iterative delivery, collaboration, and continuous learning. Requirements: Proven professional experience as a full-stack software engineer , with a track record of independently building and shipping production features in SaaS environments. Demonstrated experience using AI coding assistants such as Claude Code, Cursor, or similar tools as an integrated part of your development workflow. Strong engineering judgment and the ability to recognize when AI-generated solutions are useful, incomplete, misleading, or require deeper human analysis. Practical experience with Scala or Java on the backend and TypeScript and Angular on the frontend is highly valuable; expertise across every technology is not required, but you should be willing and able to grow across the stack. Solid understanding of SaaS architecture and cloud fundamentals , particularly within AWS environments. Experience with Docker, Kubernetes, GitHub workflows, and CI/CD pipelines . Strong understanding of software engineering principles, including clean architecture, testing, maintainability, performance, and secure development. A genuine agile mindset, with a preference for iterative delivery, rapid feedback, collaborative problem-solving, and continuous improvement.

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