{"id":571353,"url":"https://alion.io/job/snapmint-principal-engineer-search","title":"Principal Engineer - Search","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":"lead","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":{"min_usd":19500,"max_usd":49000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":14},"experience_years_min":10,"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":"Embeddings","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenSearch","optional":false},{"name":"Semantic Search","optional":false},{"name":"LLM","optional":true},{"name":"RAG","optional":true},{"name":"Recommender Systems","optional":true}],"status":"live","first_seen_at":"2026-09-09T13:03:04Z","employer_posted_date":null,"last_verified_at":"2026-09-09T13:03:04Z","board_verified":false,"closed_at":null,"days_open":54,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":54},"description":"We are looking for a Principal Engineer - Search to lead the vision, architecture, and evolution of Snapmint's Search platform. This role is responsible for building industry-leading search experiences that help millions of users discover relevant products quickly and efficiently across Snapmint's ecommerce ecosystem. As a Principal Engineer, you will drive technical strategy, mentor engineering teams, influence cross-functional product decisions, and architect highly scalable, low-latency search systems leveraging modern Information Retrieval, Machine Learning, and Generative AI technologies.\nResponsibilities:\nDefine and drive the vision, architecture, and roadmap for Snapmint's Search and Discovery platform.\nArchitect scalable, low-latency, and highly available search systems serving millions of requests.\nLead search relevance initiatives across query understanding, ranking, semantic retrieval, personalisation, and GenAI-powered search.\nDesign and optimise indexing pipelines, search APIs, and core discovery capabilities including autocomplete, recommendations, filters, and zero-result recovery.\nEstablish best practices for scalability, performance, observability, and operational excellence.\nDefine search quality metrics (CTR, Conversion, Recall, Precision, Latency) and drive continuous improvement through experimentation and A/B testing.\nPartner with Product, Data Science, Catalogue, and Personalisation teams to enhance product discoverability and customer experience.\nMentor senior engineers and provide technical leadership across the organisation.\nRequirements:\n10+ years of software engineering experience, with significant experience building large-scale Search, Discovery, Recommendation, or Information Retrieval systems.\nStrong expertise in Elasticsearch, OpenSearch, Apache Solr, or similar search technologies.\nDeep understanding of Information Retrieval fundamentals including: Inverted indexes, Tokenisation, Analysers, BM25 Query parsing, Faceting, Relevance tuning, Ranking models.\nProven experience designing and operating large-scale, distributed backend systems.\nStrong hands-on experience with query understanding systems such as spell correction, synonym management, multilingual search, transliteration, and query expansion.\nExperience building scalable search APIs and search platforms serving high-volume traffic.\nExpertise in search performance optimisation, capacity planning, caching strategies, and low-latency architecture.\nStrong knowledge of semantic search, embeddings, vector databases, and hybrid retrieval architectures.\nExperience implementing Learning-to-Rank frameworks and ML-driven ranking systems in production environments.\nDemonstrated ability to lead large technical initiatives and influence cross-functional engineering organisations.\nGood to Have:\nExperience building Search and Discovery platforms for ecommerce, fintech marketplaces, or large consumer internet products.\nExperience with Generative AI and LLM-powered search, including: Conversational search, Retrieval-Augmented Generation (RAG), Query rewriting, Search assistants, Search personalisation.\nExperience with vector databases and modern retrieval frameworks.\nFamiliarity with recommendation systems and personalisation engines.\nExperience leading organisation-wide architecture reviews and technical strategy initiatives.\nStrong track record of mentoring senior engineers and growing technical leadership within teams.\nExperience driving experimentation frameworks and relevance optimisation through A/B testing at scale.","description_format":"text","description_chars":3558,"description_truncated":false,"requirements":{"experience_years_min":10,"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 Later"],"lifecycle":[{"event":"open","at":"2026-09-09T13:03:04Z"}],"visa":[],"liveness":{"score":12,"band":"cold","label":"Long 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