Discover newly added software engineering jobs across Germany and remote teams.

Develop and maintain high-performance, data-driven systems in a distributed infrastructure that impact marketplace performance. Build and scale an online feature store and maintain robust CI/CD pipelines across testing and production environments while collaborating with data, software, and product teams to advance MLOps.

Conceive, build, and operate AI systems including Conversational AI, RAG, agents, and voice. Develop scalable multi-tenant SaaS backends and own features end-to-end from idea to production.

You will be technically responsible for the backend of our AI platform, focusing on system architecture, AI integration, and long-term product quality. You will design and evolve the Python backend, RAG architectures, AI pipelines, and agent workflows.

Design, build, and maintain backend services at the core of Smartly.io’s campaign optimization products. Support data scientists in bringing ML models to production and promote software engineering best practices.

Shape the product by owning and building frontend and backend features that streamline debugging and monitoring for developers. Collaborate with open-source contributors and customers to incorporate their feedback into our roadmap.

Build ML-based software systems enabling advertising experiences and campaigns. Contribute to Smartly’s MLOps and data platform and translate business needs into scalable ML solutions.

Design, build, and improve tools, libraries, and frameworks for the engineering team. Build and test scalable deployment tools for automotive and cloud platforms.

Architect end-to-end digital ecosystems connecting frontends, backends and AI systems through modular, API-first design. Lead cross-functional teams to design scalable architectures, document decisions, and guide security, observability and deployment practices.

Design, build, and operate Azure- and Databricks-based data platforms. Develop and optimize ETL/ELT pipelines with PySpark, Python, and SQL, operationalize ML models, and implement CI/CD for data pipelines.

Build, operate, and continuously evolve a modern Data-Lakehouse using Microsoft Fabric and Databricks. Transform and model raw data with SQL and Python (PySpark, Pandas) for reporting and analytics, develop Power BI dashboards, and design automated Make workflows and API integrations while monitoring data pipelines.