Senior Backend Engineer/Architecture/Lead -search &recommendation

Responsibilities 1. Design and evolve search infrastructure: Architect, develop, and maintain robust backend services for search and recommendation pipelines, covering data ingestion, real-time indexing, query parsing, and multi-channel retrieval. 2. Performance and latency optimization: Continually optimize query performance against massive datasets with complex real-time filters, including pricing, dynamic inventory, and geo-spatial data, to keep search latency in milliseconds during peak traffic. 3. Algorithm engineering and productionization: Partner closely with AI and algorithm scientists to productionize advanced features including NLP and tokenization, intent recognition, re-ranking, personalized recommendation, and vector search. 4. Search engine tuning: Drive performance tuning, sharding strategies, and schema mappings for Elasticsearch and OpenSearch clusters, while building comprehensive monitoring for search quality metrics. 5. Cross-regional collaboration: Coordinate with regional product and engineering teams across Singapore and Jakarta to support localization and multi-language search capabilities unique to Southeast Asian markets. Requirements 1. Bachelor's degree in Computer Science, Engineering, or a related field. 2. Professional English proficiency: Excellent verbal and written communication skills to collaborate seamlessly within a multicultural, distributed engineering team. 3. At least 8 years of backend development experience, with a solid grasp of data structures, algorithms, and distributed systems design. 4. Deep search expertise: Proven production experience with Elasticsearch, OpenSearch, Solr, or Lucene, with a deep understanding of inverted indexes, cluster tuning, and custom plugins. 5. Core technology stack: Strong proficiency in Java, Spring Boot, or JVM-centric stacks. Experience with relational databases such as PostgreSQL and MySQL, as well as stream processing tools such as Kafka and Flink, for building real-time synchronization pipelines. Preferred Qualifications 1. Direct experience in large-scale e-commerce, OTA search, recommendation, or ad-tech systems. 2. Familiarity with vector databases such as Milvus and Pinecone, or LLM-driven semantic search. 3. Background in cloud infrastructure, especially AWS, and containerization with Docker and Kubernetes.