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We are seeking a Senior Engineer with deep expertise in Apache Solr to design, build, and optimize scalable search solutions. This role focuses on improving search performance, relevancy, and indexing pipelines in a cloud-based environment. You will own search relevance across both traditional keyword-based and modern semantic (vector-based) retrieval.
Req.#989600929
Responsibilities
- Design, build, and maintain Solr-based search platforms
- Optimize search relevancy, ranking, and query performance
- Build and manage indexing pipelines for large datasets
- Deploy and operate services in AWS
- Collaborate with cross-functional teams on search and recommendation features
- Explore and implement ML-driven enhancements for search
- Define and implement hybrid search strategies combining keyword and vector-based retrieval
- Build and operate vector search pipelines within Solr/Lucene
- Measure and improve search relevance using evaluation metrics and experimentation
- Maintain Solr in production (SolrCloud), including collections, sharding, replication, and scaling
- Establish monitoring, SLOs, runbooks, and participate in incident response and root cause analysis
Requirements
- Strong experience with Apache Solr and backend development (Java or similar)
- Experience working with AWS
- Solid understanding of search architecture, indexing, and performance optimization
- Experience designing and tuning search relevance strategies
- Hands-on experience with SolrCloud in production environments
- Familiarity with vector search and modern retrieval techniques
Nice to have
- Experience with machine learning in search or recommendation systems
- Familiarity with Elasticsearch or OpenSearch
- Experience with distributed systems and large-scale data processing
- Exposure to embedding-based retrieval and approximate nearest neighbor (ANN) algorithms
- Experience with re-ranking or learning-to-rank approaches