Senior Product Manager, Content Metadata and Vectorization

Remitly • London, PA

1d

About The Position

Senior Product Manager – Content Metadata and Vectorization (Search and AI) About Elsevier Elsevier is a global leader in information, analytics, and decision support solutions for science, health, and technology professionals. We help researchers, clinicians, and educators advance knowledge and improve outcomes by delivering trusted content, data, and insights at the moments they matter most. Across healthcare, Elsevier partners with clinicians and health systems to support evidence-based decision making, education, and lifelong learning. Our clinical solutions, including ClinicalKey and ClinicalKey AI, are designed to help healthcare professionals quickly find relevant, trusted information and apply it confidently in patient care. As part of the RELX Group, Elsevier operates in a global, diverse, and collaborative environment that brings together expertise in content, technology, data science, and product innovation. We invest heavily in digital platforms, search, and AI to ensure our solutions continue to evolve alongside the needs of our users and the communities we serve. At Elsevier, we are committed to advancing inclusion, fostering curiosity, and building products that make a meaningful impact on healthcare and society. We value thoughtful problem solving, cross-functional collaboration, and a strong sense of ownership, empowering our teams to shape the future of knowledge-driven decision support. About the Role Elsevier Clinical Solutions is seeking a Senior Product Manager to own the content metadata and vectorization strategy that powers search and AI-driven experiences across ClinicalKey and ClinicalKey AI. This role is responsible for defining how clinical content is represented for machines, spanning lexical metadata, semantic embeddings, and scalable pipelines that support hybrid search and retrieval-augmented generation. The role sits at the intersection of Search, AI, Content, and Platform teams and plays a critical part in ensuring that Elsevier’s clinical content is discoverable, reliable, and usable in high-trust clinical workflows. What You Will Own Content Representation Strategy Define the product vision and strategy for content metadata and vectorization across ClinicalKey and ClinicalKey AI. Establish principles for content granularity, lexical versus semantic representation, and consistency across products and use cases. Ensure alignment between query understanding, retrieval strategies, search relevance, and AI answer quality . Content Vectorization Product Ownership Own product decisions related to semantic representation of content, including what content is embedded, appropriate levels of granularity, refresh cadence, and success metrics for vector-based retrieval. Partner with Search and AI teams to evaluate embedding approaches and make informed trade-offs between quality, cost, latency, and scalability. Define requirements to ensure vectorized content supports hybrid retrieval, RAG pipelines, and clinical explainability. Metadata and Content Tagging Strategy Own the metadata and content tagging roadmap across ClinicalKey and ClinicalKey AI. Define product requirements for clinical concept tagging, content attributes such as specialty, content type, and evidence level, and editorial or trust signals. Ensure metadata supports lexical search relevance, facets, filters, boosts, and transparency, while also enabling safety and grounding in AI outputs. Balance automated tagging approaches with editorial and subject matter expert workflows. Pipelines, Platforms, and Enablement Define product requirements for scalable pipelines that support metadata generation, content embedding, re-embedding, monitoring, and quality controls. Partner with Platform and Data teams to translate strategy into executable roadmaps and ensure consistency across ingestion paths for ClinicalKey and ClinicalKey AI. Drive prioritization across competing needs from Search, AI, and Content stakeholders. Metrics, Governance, and Quality Define and track success metrics related to metadata coverage, quality, and retrieval effectiveness across lexical and semantic systems. Establish governance frameworks for metadata standards, taxonomy changes, model updates, and the introduction of new content types. Act as the product owner and decision-maker for content representation initiatives, ensuring long-term consistency and impact. Why This Role Matters This role plays a critical part in shaping how clinical content is discovered, retrieved, and trusted across ClinicalKey and ClinicalKey AI. The decisions made in this role directly influence search relevance, AI answer quality, and the ability of clinicians to access reliable information at the point of care.

Requirements

• Five or more years of experience as a Product Manager or Senior Product Manager.
• Proven experience owning platform, data, search, or AI-adjacent products in a complex, cross-functional environment.
• Strong ability to partner effectively with Search, AI or ML engineering teams, and content or editorial organizations.
• Demonstrated ability to translate complex technical concepts into clear product strategy, requirements, and success metrics.

Nice To Haves

• Experience working on search, information retrieval, or AI-powered products.
• Familiarity with metadata systems, taxonomies, embeddings, vector search, or retrieval-augmented generation concepts.
• Experience working with clinical, biomedical, or scientific content domains.
• Background in products that require high levels of precision, trust, and explainability.

Responsibilities

• Define the product vision and strategy for content metadata and vectorization across ClinicalKey and ClinicalKey AI.
• Establish principles for content granularity, lexical versus semantic representation, and consistency across products and use cases.
• Ensure alignment between query understanding, retrieval strategies, search relevance, and AI answer quality .
• Own product decisions related to semantic representation of content, including what content is embedded, appropriate levels of granularity, refresh cadence, and success metrics for vector-based retrieval.
• Partner with Search and AI teams to evaluate embedding approaches and make informed trade-offs between quality, cost, latency, and scalability.
• Define requirements to ensure vectorized content supports hybrid retrieval, RAG pipelines, and clinical explainability.
• Own the metadata and content tagging roadmap across ClinicalKey and ClinicalKey AI.
• Define product requirements for clinical concept tagging, content attributes such as specialty, content type, and evidence level, and editorial or trust signals.
• Ensure metadata supports lexical search relevance, facets, filters, boosts, and transparency, while also enabling safety and grounding in AI outputs.
• Balance automated tagging approaches with editorial and subject matter expert workflows.
• Define product requirements for scalable pipelines that support metadata generation, content embedding, re-embedding, monitoring, and quality controls.
• Partner with Platform and Data teams to translate strategy into executable roadmaps and ensure consistency across ingestion paths for ClinicalKey and ClinicalKey AI.
• Drive prioritization across competing needs from Search, AI, and Content stakeholders.
• Define and track success metrics related to metadata coverage, quality, and retrieval effectiveness across lexical and semantic systems.
• Establish governance frameworks for metadata standards, taxonomy changes, model updates, and the introduction of new content types.
• Act as the product owner and decision-maker for content representation initiatives, ensuring long-term consistency and impact.

Benefits

• This job is eligible for an annual incentive bonus.
• We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed