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commercetools is a leading commerce platform company that powers product discovery and commerce innovation for the world's most ambitious enterprises. As a Senior Search Backend Engineer on the Discovery Team, you will design and build the retrieval layer behind product discovery for demanding commerce brands at scale.
The role focuses on modernizing search capabilities as customer behavior evolves—shoppers now type full sentences instead of keywords, and AI agents increasingly call the API rather than humans. You will work across the full stack of search technology, from query understanding through vector indexing to query cost optimization, taking semantic and hybrid retrieval from development to general availability.
Key responsibilities include:
- Design and implement search functionalities in a PaaS ecommerce Scala backend
- Develop search capabilities combining lexical, semantic, and hybrid retrieval approaches
- Build and maintain search-related libraries based on Elasticsearch and MongoDB
- Contribute to search relevance measurement and quality metrics
- Run and maintain scalable search infrastructure as code on Kubernetes using Terraform and multi-tenant architecture
- Test software components for usability, functionality, and performance in collaboration with Product and DevOps
- Learn Scala and functional programming as primary development tools
- Participate in on-call rotation with a globally distributed team for production systems
This is a hybrid role requiring three days per week in the Munich, Berlin, London, or Valencia office.
REQUIREMENTS:
- Minimum 5 years of experience as a Software Engineer with production JVM experience
- Solid understanding of parallel and asynchronous programming, non-blocking I/O
- Experience developing REST APIs and knowledge of scalable architectures (sharding, replication, load balancing, failover)
- Interest in working with Scala using pragmatic functional programming patterns (support provided if coming from another JVM language)
- Fluent English for international team collaboration
- Experience operating multi-tenant SaaS systems where one tenant's load must not affect another's
- Knowledge of scalable event-driven architectures including queues and notification topics
- Genuine curiosity for using AI tools to work smarter and willingness to learn and apply them in the role
NICE TO HAVE:
- Hands-on search experience with Elasticsearch or OpenSearch, including understanding of inverted index scoring and ranking
- Practical exposure to vector retrieval (embeddings, approximate nearest neighbor indexes, hybrid ranking)
- Ability to reason about relevance using data (precision/recall tradeoffs, ranking metrics, behavioral signals)
- Experience with infrastructure technologies like Helm, Kubernetes, and Rust
