Senior Search Engineer - OpenSearch in भारत

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Search Engineer - OpenSearch based in India. This role focuses on building advanced search capabilities that help users quickly find materials, customers, orders, and documents across massive enterprise datasets. You will play a key role in designing and optimizing search infrastructure built around OpenSearch and modern relevance techniques. The position combines product engineering with hands-on delivery, allowing you to shape platform capabilities while solving customer-specific search challenges. You will work across index and schema design, ingestion pipelines, query optimization, relevance engineering, and search APIs. A major focus will be applying strong technical judgment to improve search quality, performance, scalability, and reliability. You will collaborate with product, implementation, solution engineering, IT, and customer teams in a technically diverse environment. The role is ideal for a senior search specialist who enjoys solving complex search problems and turning measurable improvements into production-ready capabilities. Accountabilities: - Design index mappings, analyzers, and sharding strategies suited to large, high-cardinality enterprise catalogs. - Build and maintain indexing pipelines that synchronize search data with SAP source systems, including full reindexing and incremental update processes. - Design and optimize queries using query DSL, scoring and boosting, synonyms, stemming, fuzzy and typo tolerance, faceting, and aggregations. - Develop and apply relevance measurement approaches to demonstrate whether search improvements produce measurable gains. - Support customer delivery engagements by profiling catalogs, tuning index and query configurations, and addressing customer-specific relevance requirements. - Diagnose and resolve search performance issues involving expensive queries, mapping and analyzer design, sharding decisions, and data modeling.

- Implement vector and hybrid search alongside lexical search when semantic matching can measurably improve results. - Define platform requirements such as cluster sizing, configuration, index lifecycle policies, snapshot strategies, and upgrade requirements. - Build clean, reliable, and well-documented search APIs for a TypeScript-based product stack. - Define search health, quality, and performance signals that the platform should monitor and surface. - Collaborate with product management on search roadmap priorities and with solution engineering on multi-tenant architecture considerations. - Document search architecture and relevance decisions so engineering teams can understand and maintain the underlying design. - Review search-related work from teammates and contribute to higher standards for query design, relevance engineering, and technical rigor. Requirements: - Deep hands-on expertise with OpenSearch or Elasticsearch, ideally including production search systems that you have personally designed and built. - Strong command of query DSL, mappings, analyzers, aggregations, and the various mechanisms that influence search relevance. - Proven experience in relevance engineering, including the ability to demonstrate and measure improvements in search quality. - Strong understanding of how index and cluster architecture affects performance, including sharding, mapping design, query cost, and Lucene fundamentals. - Excellent debugging skills for slow or expensive queries, mapping and analyzer issues, and search results that fail to meet user expectations. - Experience building high-throughput ingestion and indexing pipelines connected to systems of record. - Proficiency in TypeScript, JavaScript, and/or Python for developing services, pipelines, and search tooling. - Comfortable working directly with customers and delivery teams to understand requirements and solve search problems.