Senior Product Manager – Enterprise Search

Accountabilities

• Own the product vision, strategy, and roadmap for enterprise search across conversational AI experiences and traditional platform search.

• Define product requirements, user stories, success metrics, and priorities around search relevance, freshness, coverage, trust, and usability.

• Lead the strategy for structured and unstructured data ingestion, collaborating with AI and search engineering teams on parsing, chunking, indexing, and embedding pipelines.

• Drive product decisions across lexical, semantic, vector, and hybrid retrieval, including re-ranking, filtering, permission-aware retrieval, latency, scalability, and cost considerations.

• Define how retrieved content is used to generate reliable AI responses through RAG, including context assembly, chunk selection, citations, grounding, and hallucination mitigation.

• Establish evaluation frameworks for search and RAG quality, including golden query sets, offline and online evaluations, and LLM-based evaluation approaches.

• Define and monitor product metrics covering relevance, precision and recall, latency, adoption, reliability, cost, and business impact.

• Ensure enterprise-grade security throughout the search experience, including document-level permissions, access controls, tenant isolation, and data governance.

• Collaborate with AI engineers, search and ML engineers, data scientists, designers, and other stakeholders to translate complex technical capabilities into scalable product experiences.

• Serve as the internal subject-matter expert for enterprise search and support customer-facing teams such as Customer Success, Sales, Support, and Marketing with search-related expertise.

• Establish feedback loops and continuous improvement processes that use customer behavior, evaluation results, and production performance to improve search and RAG quality.

• Stay current with advances in enterprise search, information retrieval, generative AI, and AI-native workplace experiences.

Requirements

• 5+ years of enterprise SaaS product management experience, including at least 2 years focused on search, information retrieval, AI, or ML-powered products.

• Bachelor's or advanced degree in Computer Science, Engineering, Data Science, or a related technical discipline.

• Deep technical understanding of the modern search stack, including ingestion, chunking, indexing, embeddings, vector databases, and lexical, semantic, and hybrid retrieval.

• Strong understanding of LLM and RAG concepts, including context assembly, grounding, citations, chunk selection, and approaches for reducing hallucinations.

• Experience developing or managing evaluation frameworks for search or RAG systems and using metrics such as relevance, precision, recall, latency, adoption, and business impact to guide product decisions.

• Working knowledge of enterprise security concepts, including access controls, permission-aware retrieval, tenant isolation, and data governance in multi-tenant SaaS environments.

• Experience with enterprise search, knowledge retrieval, or RAG-powered products, particularly within SaaS, collaboration, productivity, or enterprise software environments.

• Familiarity with search technologies such as Elasticsearch, OpenSearch, Solr, Lucene, Pinecone, Weaviate, pgvector, or comparable managed search and vector solutions.

• Experience designing relevance-tuning workflows, feedback loops, or evaluation systems that continuously improve search quality in production.

• Strong product strategy and roadmap development capabilities, with the ability to translate complex technical concepts into clear priorities and measurable outcomes.

• Excellent communication and collaboration skills, with the ability to work effectively with both highly technical teams and non-technical stakeholders.

• Strong customer orientation and an understanding of how enterprise users discover, consume, and trust organizational knowledge.

• Ability to operate effectively in a fast-moving environment while balancing technical complexity, customer needs, security requirements, and business priorities.

• Passion for AI-native products and improving how people access trustworthy enterprise knowledge through intelligent assistants and search experiences.

Benefits

• Opportunity to own the strategy and roadmap for a critical enterprise search and AI product area.

• High-impact role at the intersection of enterprise SaaS, search, information retrieval, and generative AI.

• Direct collaboration with AI engineers, search and ML specialists, data scientists, designers, and cross-functional product teams.

• Opportunity to shape AI-powered employee experiences and enterprise knowledge discovery.

• Exposure to advanced technologies including vector search, hybrid retrieval, embeddings, LLMs, and RAG.

• Significant ownership over product strategy, evaluation frameworks, and measurable customer outcomes.

• Flexible working model with the opportunity to work from the Bengaluru or Gurugram locations according to role requirements.

• Collaborative environment with opportunities to work across Product, Engineering, Customer Success, Sales, Support, and Marketing.

• Opportunity to influence how enterprise customers securely discover and interact with organizational knowledge.

• Career growth opportunities within a rapidly evolving AI and enterprise software environment.