Principal Member of Technical Staff - Java + Node.Js (GenAI search)
Salesforce, Inc. (company site, opens in a new tab)10+ yrsBengaluruOn-siteDirect career pageEst. 50–90 LPA
Posted 9h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead architectural design and delivery of next-generation AI-powered Search and Personalization systems, including multi-turn conversational search, AI overviews, query suggestions, and contextual discovery.
- Own technical vision and engineering excellence for scalable, low-latency search indexing pipelines, embedded discovery surfaces, and personalization services within AgentExchange across multiple product platforms.
- Drive AI-native engineering adoption, mentor engineering teams, ensure reliability (99.95% availability), security governance, and collaborate cross-functionally to align on discovery infrastructure and catalog indexing.
Minimum Requirements
- 10+ years of software engineering experience with demonstrated technical leadership on enterprise-scale search, recommendation, or personalization systems.
- Strong expertise with search engine internals, including indexing, ranking, query understanding, and use of search infrastructure like Elasticsearch, OpenSearch, or Solr.
- Proficiency in back-end development using Node.js and Java or equivalent technologies for high-throughput search services.
- Hands-on experience integrating GenAI or large language models into search products with AI-generated summaries, semantic search, or conversational retrieval.
Ideal Candidate Profile
- Experienced leader capable of defining and driving long-term technical vision and architecture for complex search and ML-infused platforms in large-scale enterprise environments.
- Proven track record building and operating multi-turn conversational search, personalization at scale, and embedded contextual discovery within SaaS or marketplace ecosystems.
- Comfortable working in a cloud-native platform modernization context with strong security and reliability mindset, influencing cross-functional teams, and fostering an AI-native engineering culture.