Full-Stack Engineer

About the Role

This is a hands-on, high-ownership engineering role on a small, product-focused team building AI-powered sales automation software for distributors and manufacturers. You will work end-to-end across the stack, from frontend interfaces to backend data pipelines, and your work will directly shape the core product.

What You'll Do

• Own the architecture and design of AI systems from the ground up.
• Collaborate with engineers across the full stack to ship complex web applications.
• Build data pipelines to process large-scale unstructured data efficiently.
• Deploy and manage software in cloud environments.
• Make the backend scalable, stable, and efficient.
• Develop scalable, reusable components and API structures.
• Write clean, maintainable code with sensible test coverage.

What We're Looking For

• At least 2 years of full-time professional engineering experience; working-student or internship-only backgrounds do not qualify.
• Strong backend-leaning full-stack profile, not a frontend-focused engineer.
• Proficiency building end-to-end AI-powered web applications using Next.js/React on the frontend and Python on the backend.
• Experience designing scalable APIs and reusable backend structures.
• Experience building data pipelines for large-scale unstructured data.
• Proficiency with PostgreSQL and relational data modeling.
• Experience with cloud platforms (AWS, Azure, or GCP) and modern CI/CD practices.
• Strong experience with Docker and Kubernetes for containerization and deployment.
• Hands-on experience with ML/NLP technologies, including embeddings, vector databases, and RLHF, as well as deploying ML components in production.
• Experience with ML model serving and inference pipelines in production environments.
• A product-minded mindset with a proven track record of shipping complex web applications.

Compensation & Benefits

Salary range

80,000 to 130,000 EUR per year. Visa sponsorship is not available for this role.

Location

On-site in Munich, Bavaria, Germany. Candidates must be willing and able to work in person on a full-time basis; limited hybrid schedules are not accommodated.