Principal Engineer - Search

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.

Responsibilities:

• Define and drive the vision, architecture, and roadmap for Snapmint's Search and Discovery platform.
• Architect scalable, low-latency, and highly available search systems serving millions of requests.
• Lead search relevance initiatives across query understanding, ranking, semantic retrieval, personalisation, and GenAI-powered search.
• Design and optimise indexing pipelines, search APIs, and core discovery capabilities including autocomplete, recommendations, filters, and zero-result recovery.
• Establish best practices for scalability, performance, observability, and operational excellence.
• Define search quality metrics (CTR, Conversion, Recall, Precision, Latency) and drive continuous improvement through experimentation and A/B testing.
• Partner with Product, Data Science, Catalogue, and Personalisation teams to enhance product discoverability and customer experience.
• Mentor senior engineers and provide technical leadership across the organisation.

Requirements:

• 10+ years of software engineering experience, with significant experience building large-scale Search, Discovery, Recommendation, or Information Retrieval systems.
• Strong expertise in Elasticsearch, OpenSearch, Apache Solr, or similar search technologies.
• Deep understanding of Information Retrieval fundamentals including: Inverted indexes, Tokenisation, Analysers, BM25 Query parsing, Faceting, Relevance tuning, Ranking models.
• Proven experience designing and operating large-scale, distributed backend systems.
• Strong hands-on experience with query understanding systems such as spell correction, synonym management, multilingual search, transliteration, and query expansion.
• Experience building scalable search APIs and search platforms serving high-volume traffic.
• Expertise in search performance optimisation, capacity planning, caching strategies, and low-latency architecture.
• Strong knowledge of semantic search, embeddings, vector databases, and hybrid retrieval architectures.
• Experience implementing Learning-to-Rank frameworks and ML-driven ranking systems in production environments.
• Demonstrated ability to lead large technical initiatives and influence cross-functional engineering organisations.

Good to Have:

• Experience building Search and Discovery platforms for ecommerce, fintech marketplaces, or large consumer internet products.
• Experience with Generative AI and LLM-powered search, including: Conversational search, Retrieval-Augmented Generation (RAG), Query rewriting, Search assistants, Search personalisation.
• Experience with vector databases and modern retrieval frameworks.
• Familiarity with recommendation systems and personalisation engines.
• Experience leading organisation-wide architecture reviews and technical strategy initiatives.
• Strong track record of mentoring senior engineers and growing technical leadership within teams.
• Experience driving experimentation frameworks and relevance optimisation through A/B testing at scale.