Senior Search Engineer

We are looking for a Search Engineer who is passionate about solving complex search problems at scale, from understanding natural, multilingual, and conversational user queries to delivering highly relevant, personalised search results across Snapmint's ecommerce ecosystem.

Responsibilities:

• Design and build scalable, low-latency Search and Discovery services capable of serving millions of search requests.
• Develop intelligent query understanding capabilities including spell correction, synonym expansion, transliteration, multilingual query processing, intent detection, query rewriting, and attribute extraction.
• Build and optimise indexing pipelines to continuously synchronise search indexes with catalogue, pricing, inventory, and merchant updates.
• Design and improve search relevance using lexical search (BM25), semantic search, Learning-to-Rank, business signals, and personalisation.
• Build search capabilities including autocomplete, query suggestions, facets, filters, zero-result recovery, and related search recommendations.
• Partner with Catalogue, Personalisation, Data Science, and Product teams to improve product discoverability and search quality.
• Define, monitor, and improve search quality metrics such as CTR, Conversion Rate, Zero-Result Rate, Recall, and Search Latency through experimentation and A/B testing.
• Drive architecture, performance optimisation, observability, and production excellence for the Search platform.

Requirements:

• 5+ years of experience designing and building scalable backend systems using modern programming languages (Java / Node.js / Rust / Golang, etc. ).
• Strong hands-on experience with Elasticsearch, OpenSearch, or Apache Solr.
• Deep understanding of Information Retrieval concepts including inverted indexes, analysers, tokenisation, BM25 faceting, query parsing, indexing, and relevance tuning.
• Experience building query understanding systems, including multilingual or transliterated search, spell correction, synonym expansion, and query normalisation.
• Experience designing scalable search APIs.
• Experience building indexing pipelines for large-scale catalogues with near real-time updates.
• Experience implementing query understanding capabilities such as spell correction, synonym expansion, query normalisation, transliteration, and attribute extraction.
• Good understanding of semantic search, embeddings and hybrid lexical-semantic retrieval.
• Experience with Learning-to-Rank (LTR) techniques or integrating ML-based ranking models into production search systems.
• Strong understanding of distributed systems, search performance optimisation, caching strategies, and low-latency system design.

Preferred Skills:

• Experience building ecommerce or marketplace search.
• Experience using LLMs for query understanding, query rewriting, or conversational search.
• Experience running online experiments and A/B testing to improve search relevance.

Skills

Apache Solr, BM25, Elasticsearch, Indexing, OpenSearch, Search, Solr, relevance