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.