Senior Search Engineer - OpenSearch in India at Jobgether

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.

• 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.
• Experience collaborating with separate platform or IT teams by clearly specifying requirements, handing over solutions, and participating in technical diagnosis.
• Strong written and verbal communication skills, with a habit of documenting technical decisions and relevance trade-offs.
• Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.
• Experience with vector and semantic search, including embeddings, OpenSearch k-NN, hybrid ranking, or learning-to-rank, is preferred.
• Familiarity with OpenSearch Dashboards, Data Prepper, Logstash, or Kafka-based ingestion is a plus.
• Experience working with SAP or ERP material master and catalog data, including part numbers, cross-references, and unit-of-measure complexity, is advantageous.
• Knowledge of query understanding techniques such as entity extraction, intent classification, spell correction, and autocomplete is a plus.
• Experience designing multi-tenant search architectures and tenant data isolation is preferred.
• Customer-facing implementation, delivery, or professional services experience is advantageous.
• Working knowledge of containers and Kubernetes is a plus.
• Contributions to OpenSearch, Lucene, or other open-source search projects are valued.

Benefits:

• Fully remote working environment.
• Full-time contractor position.
• Opportunity to design and build search capabilities used across large-scale enterprise datasets.
• Combination of product engineering and customer-facing delivery work.
• Hands-on exposure to OpenSearch, relevance engineering, indexing pipelines, and hybrid search.
• Opportunity to solve complex challenges involving scalability, performance, data quality, and multi-tenant architecture.
• Collaboration with product, engineering, implementation, solution engineering, IT, and customer teams.
• Opportunity to contribute to technical standards and search architecture decisions.