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.