About the Role
This is a hands-on, high-ownership engineering role at a fast-growing AI startup automating sales workflows for distributors and manufacturers. You'll build end-to-end AI-powered systems — from data pipelines and backend services to polished frontend experiences — and help shape the technical direction of the product from an early stage.
What You'll Do
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Own the architecture and design of AI systems, making key technical decisions with clear documentation and code quality standards.
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Collaborate across the full stack with a tight-knit team of engineers.
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Build and maintain data pipelines to process large-scale unstructured data efficiently.
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Deploy and manage software in cloud environments, ensuring reliability and scalability.
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Make the backend scalable, stable, and performant.
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Develop reusable frontend components and well-structured API layers.
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Write clean, maintainable code backed by thoughtful unit and integration testing strategies.
What We're Looking For
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Proficiency building end-to-end AI-powered web applications with Next.js/React and TypeScript on the frontend and Python on the backend.
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Strong experience with Docker and Kubernetes for containerization and deployment.
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Hands-on experience with cloud platforms (AWS, Azure, or GCP) and modern CI/CD practices.
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Experience designing and implementing scalable RESTful APIs for production web applications.
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Proficiency with PostgreSQL and relational data modeling.
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A product-minded approach with a demonstrable track record of shipping complex web applications.
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Experience building and validating testing strategies, including unit and integration tests.
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Hands-on experience with ML/NLP technologies — including embeddings, vector databases, and RLHF — and deploying ML components in production.
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Experience with ML model serving and inference pipelines in production environments is a plus.
Compensation & Benefits
Salary range: €90,000 – €200,000 per year. Visa sponsorship is not available for this role.
Location
On-site in Munich, Bavaria, Germany. No remote option.
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