Principal Product Mgr I

Overview

In this role you drive the strategy and delivery of the agentic retrieval and orchestration engine at LeapSpace, the AI-powered research workspace from Elsevier. You lead cross-team decisions as the engine migrates from prototype to production, aligning platform needs with product roadmaps and external dependencies. You shape the next generation of AI-assisted research, working closely with engineers, data scientists, and senior product leadership. This is a highly technical, impact‑driven opportunity to scale a core capability across multiple squads and partner teams.

Pay / Benefits

• Generous holiday allowance
• Health screening and private medical benefits
• Wellbeing programs
• Life assurance
• Contributory pension scheme
• Sabbaticals

Responsibilities

• Own the product strategy, vision, and roadmap for agentic retrieval and orchestration
• Make sequencing calls across teams to determine what ships first and manage dependencies
• Lead migration of engine capabilities from prototype to production with staged releases
• Translate prototype behavior into engineering-ready tickets with clear acceptance criteria
• Keep impacted teams informed ahead of changes and plan for downstream effects
• Support squads by consolidating agentic requests into shared platform capabilities
• Anticipate roadmap-driven demand and position the engine accordingly
• Expand LeapSpace surface area by growing tools, skills, and aligned user tasks across the platform
• Collaborate with Elsevier partner teams to extend capabilities and reach across products

Key requirements

• 10+ years building and shipping complex AI or data-intensive products with ownership of strategy, trade-offs, discovery, and delivery
• Deep expertise in generative AI products, including retrieval-augmented generation and agentic workflows
• Ability to independently drive product strategy and execution across multiple engineering organizations and external dependencies
• Strong go-to-market experience
• Hypothesis-driven product evaluation with data-driven culture facilitation (A/B testing, experimentation)
• Comfort with AI coding tools and rapid prototyping alongside engineering and data science teams
• Experience in customer discovery in academic, research, or professional information markets is desirable
• Technically fluent with sound architectural judgment and ability to engage with architects, AI researchers, engineers, and platform teams

• stakeholder management
• data-driven decision making
• curiosity about new ideas and technologies
• generative AI
• retrieval-augmented generation
• agentic workflows

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