{"id":928586,"url":"https://alion.io/job/snapmint-senior-search-engineer","title":"Senior Search Engineer","company":{"id":809,"name":"Snapmint","domain":"snapmint.com","url":"https://alion.io/company/snapmint","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Apache Solr","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Node JS","optional":false},{"name":"OpenSearch","optional":false},{"name":"Rust","optional":false},{"name":"Semantic Search","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-09-15T09:45:16Z","employer_posted_date":null,"last_verified_at":"2026-09-15T09:45:16Z","board_verified":false,"closed_at":null,"days_open":46,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":46},"description":"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.\n\nResponsibilities: \nDesign and build scalable, low-latency Search and Discovery services capable of serving millions of search requests.\nDevelop intelligent query understanding capabilities including spell correction, synonym expansion, transliteration, multilingual query processing, intent detection, query rewriting, and attribute extraction.\nBuild and optimise indexing pipelines to continuously synchronise search indexes with catalogue, pricing, inventory, and merchant updates.\nDesign and improve search relevance using lexical search (BM25), semantic search, Learning-to-Rank, business signals, and personalisation.\nBuild search capabilities including autocomplete, query suggestions, facets, filters, zero-result recovery, and related search recommendations.\nPartner with Catalogue, Personalisation, Data Science, and Product teams to improve product discoverability and search quality.\nDefine, monitor, and improve search quality metrics such as CTR, Conversion Rate, Zero-Result Rate, Recall, and Search Latency through experimentation and A/B testing.\nDrive architecture, performance optimisation, observability, and production excellence for the Search platform.\n\nRequirements: \n5+ years of experience designing and building scalable backend systems using modern programming languages (Java / Node.js / Rust / Golang, etc. ).\nStrong hands-on experience with Elasticsearch, OpenSearch, or Apache Solr.\nDeep understanding of Information Retrieval concepts including inverted indexes, analysers, tokenisation, BM25 faceting, query parsing, indexing, and relevance tuning.\nExperience building query understanding systems, including multilingual or transliterated search, spell correction, synonym expansion, and query normalisation.\nExperience designing scalable search APIs.\nExperience building indexing pipelines for large-scale catalogues with near real-time updates.\nExperience implementing query understanding capabilities such as spell correction, synonym expansion, query normalisation, transliteration, and attribute extraction.\nGood understanding of semantic search, embeddings and hybrid lexical-semantic retrieval.\nExperience with Learning-to-Rank (LTR) techniques or integrating ML-based ranking models into production search systems.\nStrong understanding of distributed systems, search performance optimisation, caching strategies, and low-latency system design.\n\nPreferred Skills: \nExperience building ecommerce or marketplace search.\nExperience using LLMs for query understanding, query rewriting, or conversational search.\nExperience running online experiments and A/B testing to improve search relevance.\nSkills\nApache Solr, BM25, Elasticsearch, Indexing, OpenSearch, Search, Solr, relevance","description_format":"text","description_chars":2992,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Buy Now, Pay 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