Senior Backend Engineer (Java)

We are looking for a highly skilled Senior Backend Engineer (Search) to design, build, and optimise large-scale search and discovery systems for e-commerce platforms. The ideal candidate should have strong experience in backend engineering, distributed systems, search technologies, and relevance optimisation, with expertise in building low-latency, high-throughput services. You will work closely with data scientists, ML engineers, product managers, and frontend teams to improve search relevance, ranking quality, query understanding, and overall customer discovery experience. Responsibilities - Design and develop scalable backend services powering search, ranking, recommendation, and discovery systems. - Build and optimise APIs and microservices for high-performance search experiences. - Develop robust pipelines for ingestion, indexing, and real-time search updates. - Collaborate with ML and data science teams to productionise ranking and recommendation models. - Optimise latency, throughput, and reliability of search infrastructure and distributed systems. - Implement monitoring, observability, alerting, and debugging mechanisms for search systems. - Drive engineering best practices, including code quality, testing, CI/CD, documentation, and system design reviews. - Mentor junior engineers and contribute to architectural decisions across the platform. Requirements - 5+ years of experience in backend software engineering. - Strong proficiency in one or more backend languages such as Java, Kotlin, Python, Go, or Scala. - Strong understanding of distributed systems, microservices architecture, and scalable backend design. - Experience designing REST/gRPC APIs and asynchronous event-driven systems. - Solid understanding of search concepts, including indexing, ranking, relevance, tokenisation, faceting, and query optimisation. - Experience working with cloud platforms such as AWS, GCP, or Azure. - Familiarity with Kafka, Pub/Sub, Redis, caching strategies, and real-time processing systems. - Strong SQL and data modelling skills. - Experience with observability tools, logging, and performance tuning. Good To Have - Experience with vector search, semantic search, embeddings, or LLM-powered retrieval systems. - Hands-on experience working with Elasticsearch/Qdrant or any other search engine. - Exposure to recommendation systems and personalisation. - Experience in e-commerce search or large-scale consumer platforms. - Familiarity with ML ranking pipelines and A/B experimentation frameworks. This job was posted by Priyanka R N from Falabella.

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