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.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

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