commercetools - Senior Search Backend Engineer

• Design and implement search functionalities in a PaaS ecommerce Scala backend • Develop search capabilities that combine lexical, semantic, and hybrid retrieval • Develop search-related libraries based on ElasticSearch and MongoDB • Contribute to search relevance and quality, and to how we measure it • Run and maintain a scalable search “infrastructure as code” on top of Kubernetes using terraform and multi-tenant architecture • Test software components regarding usability, functionality, and performance, and work closely with Product Management and DevOps • Learn Scala and functional programming as your new main development tools • Take part in on-call rotation with a worldwide distributed team for production systems • This role is hybrid, with three days a week spent in our Munich, Berlin, London or Valencia office. • Munich, Berlin, London or Valencia • What Sets You Apart • What Sets You Apart • You're a creative problem-solver who is wired to find solutions. You confidently dive into complex challenges and have a talent for making them simple for others. Your curiosity drives you to constantly grow and contribute to an environment of trust and teamwork. • Great ideas come from many paths, and your unique perspective matters more than checking every box. What matters most is the mindset you bring to the work. You do not need to be an ML researcher for this role. You need to be a strong backend engineer who is genuinely interested in retrieval quality. • At least 5 years of experience as a Software Engineer, with production experience on the JVM • Solid understanding of parallel and asynchronous programming, as well as non-blocking I/O • Experience developing REST APIs and knowledge of scalable architectures, including sharding, replication, load balancing, and failover • Interest in working with Scala using pragmatic functional programming patterns. If you come from another JVM language, we will support you in picking it up. • Fluent English for work in international teams • Experience operating multi-tenant SaaS where one tenant’s load must never affect another’s • Knowledge of scalable event-driven architectures, including queues and notification topics • A genuine curiosity for using AI tools to work smarter and more effectively, paired with a drive to learn and put them into practice in your role. • Hands-on search experience, preferably ElasticSearch or OpenSearch, including a working understanding of how an inverted index scores and ranks documents • Practical exposure to vector retrieval, such as embeddings, approximate nearest neighbor indexes, and hybrid ranking, and a sense of where each approach breaks down. A deep lexical search background plus a clear appetite to go into this territory also works. • Comfort reasoning about relevance with data, including precision and recall tradeoffs, ranking metrics, and behavioral signals • Experience with infrastructure work and other technologies like Helm, Kubernetes, and Rust