Staff Engineer

We are looking for a Senior Software Developer / Staff Engineer to build and scale Snapmint's Search and Discovery platform across its e-commerce ecosystem. The role will own search relevance, query understanding, indexing, and ranking systems, enabling fast, personalised, and highly relevant product discovery at scale.
Responsibilities:
Own the architecture and evolution of high-scale, low-latency Search and Discovery services, serving millions of search requests with strong reliability and performance.
Build query understanding systems covering spell correction, synonym expansion, transliteration, multilingual search, intent detection, query rewriting, and attribute extraction.
Own near-real-time catalogue indexing pipelines to keep search indexes synchronised with catalogue, pricing, inventory, and merchant updates.
Drive search relevance and ranking using BM25 semantic search, Learning-to-Rank, business signals, and personalisation.
Build and improve search experiences including autocomplete, query suggestions, facets, filters, zero-result recovery, and related searches.
Partner with Catalogue, Personalisation, Data Science, and Product teams to improve product discoverability and search quality.
Define and optimise search metrics such as CTR, conversion rate, zero-result rate, recall, and latency through experimentation and A/B testing.
Drive architecture, scalability, observability, performance optimisation, and production excellence for the Search platform.
Requirements:
5+ years of experience building scalable backend systems using modern programming languages.
Strong hands-on experience with Elasticsearch, OpenSearch, or Apache Solr.
Deep understanding of Information Retrieval, including inverted indexes, analysers, tokenisation, BM25 faceting, query parsing, indexing, and relevance tuning.
Experience building query understanding systems, including spell correction, synonym expansion, query normalisation, transliteration, and attribute extraction.
Experience designing scalable search APIs and near-real-time indexing pipelines for large product catalogues.
Understanding semantic search, embeddings, and hybrid lexical-semantic retrieval.
Experience with Learning-to-Rank or ML-based ranking models in production search systems.
Strong understanding of distributed systems, caching, search performance optimisation, and low-latency system design.
Good to Have:
Experience building e-commerce or marketplace search systems.
Experience using LLMs for query understanding, query rewriting, or conversational search.
Experience running online experiments and A/B testing to improve search relevance and business metrics.

Skills
API, Elasticsearch, OpenSearch, Solr, backend, caching, distributed, indexing, ranking, relevance, retrieval, search

Experience
6-10 yrs