Elsevier
Principal Product Mgr I
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Principal Product Manager I
Do you have 10+ years building and shipping complex AI or data-intensive products? Do you have a real passion for new ideas, techniques, and technologies? Join us and lead the future of AI-powered research at LeapSpace!
Location: UK
About our Team
We build LeapSpace, an AI-assisted workspace where researchers find scientific literature they can trust and do their best thinking and work in one place. It incorporates Scopus, peer-reviewed full-text articles, and a growing set of other sources.
We're an international team and we work from evidence. We support science to help improve the world.
About the Role
We're looking for a Principal Product Manager to own agentic retrieval and orchestration for LeapSpace: the engine at the heart of the product.
Every answer LeapSpace gives runs through this engine, from planning the research approach to orchestrating the tools and models that turn a question into a referenced answer. The next generation will plan its own research more deeply and reason over more kinds of sources. It will answer questions we cannot answer today. You will shape its direction and sequencing in partnership with the Senior Director of Product Management and Strategy, and carry those decisions across the teams that build it. That partnership will be close initially, with your ownership growing as delivery matures.
This is the most technical product role on LeapSpace. You will work with a dedicated team focused on shared GenAI capabilities, whose engineers and data scientists are drawn from multiple product squads and platform teams. The engine also spans an AI orchestration platform team and production UI teams, so most significant decisions cross at least one team boundary, and several involve dependencies you will manage rather than own: platform prerequisites, data access, and legal and privacy review. We are looking for someone who can frame the problem and make the call, and who holds the sequence together when priorities shift.
The engine's next generation already exists as a working, validated prototype. A large part of this role is leading its staged migration into production. You will decide what ships in each increment, set the interim targets that reduce the size of each subsequent step, and keep the engineering backlog defined well ahead of the team's capacity. This is hands-on delivery leadership, carried out in refinement with engineers and data scientists, rather than programme oversight at a distance.
The engine is also a shared service. Other LeapSpace squads build their agentic features on it, and part of the role is serving them well: gathering their requirements, recognising when several teams need the same capability, and consolidating that demand into shared platform work. You will also anticipate what the product roadmap will require of the system before the requirement arrives.
The engine is also how LeapSpace grows. New tools and skills extend the product to new user tasks, often built in partnership with other Elsevier teams. You will own that expansion: which capabilities come next, for which users, and with which partners.
You will report to the VP of Product Management and work closely, day to day, with the Senior Director of Product Management and Strategy for LeapSpace. We expect product managers to stay close to the technology: to understand how the AI behaves, how it is evaluated, and where the trade-offs lie. You will validate concepts by prototyping alongside engineers and data scientists, but the craft we hire for is product judgment.
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This field moves quickly, and we expect genuine curiosity about it. The right person follows new ideas, techniques, and technologies as they emerge, tests them independently through their own research, and brings informed opinions to decisions rather than waiting for the team to evaluate everything first.
Responsibilities
- Own the product strategy, vision, and roadmap for agentic retrieval and orchestration. The near-term features are how that strategy shows up, not the strategy itself.
- Make the sequencing calls that span teams (what ships first, what waits on a dependency, what each answer costs) and carry them across the teams involved.
- Lead the migration of new engine capabilities from prototype to production: stage the releases, set interim targets, lock versions and route further experiments to the next one.
- Translate validated prototype behaviour into engineering-ready work: tickets with clear acceptance criteria and a technical approach, refined with the team until each increment can be built without further clarification.
- Keep the teams that build on the engine informed ahead of change. Engine changes affect every squad as well as UX, design, and data science. Brief each group early, in terms relevant to its work, so downstream teams can plan for changes rather than discover them.
- Support the other squads with their agentic requirements: bring their requests into the engine's backlog, and identify the common needs worth building once as platform capability rather than repeatedly as separate features. When a new request displaces committed work, make the trade-off explicit.
- Anticipate demand on the agentic system from the product roadmap (new sources, new output forms, new workflows) and position the engine ahead of what LeapSpace will need next.
- Expand LeapSpace's surface area through the engine. Grow its tools and skills, and consolidate the user tasks and personas they serve so the catalogue remains coherent as it grows. Collaborate with partner teams across Elsevier on capabilities that span products.
Requirements
- 10+ years building and shipping complex AI or data-intensive products, including sustained ownership of strategy, trade-offs, discovery, and delivery. At least three consecutive years at one employer. The substance of this experience matters more than the job title: strong candidates may come from product management, engineering leadership, or applied AI backgrounds.
- Deep expertise in generative AI products, including retrieval-augmented generation, agentic workflows, and how they are evaluated. This is central to the role.
- Proven ability to independently drive product strategy and execution across multiple engineering organisations and external dependencies.
- Strong go-to-market experience.
- Skilled at driving hypothesis-driven product evaluation, including A/B testing and experimentation frameworks; able to foster a data-driven culture across the team.
- Comfortable with AI coding tools and rapid prototyping; able to build proofs of concept and validate ideas alongside engineering and data science teams.
- Experience in customer discovery in academic, research, or professional information markets is highly desirable.
- Technically fluent, with sound architectural judgment. You can reason about system boundaries and trade-offs, contribute substantively to architecture discussions, and engage credibly with architects, AI researchers, engineers, and platform teams.
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Work in a way that works for you
We promote a healthy work/life balance across the organisation. With an average length of service of 9 years, we are confident that we offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
- Working in a hybrid way from both the office and at home
- Working flexible hours - flexing the times you work in the day
Working with us
We are an equal opportunity employer with a commitment to help you succeed. Here, you will find an inclusive, agile, collaborative, innovative and fun environment, where everyone has a part to play. Regardless of the team you join, we promote a diverse environment with co-workers who are passionate about what they do, and how they do it.
Working for you
At Elsevier, we know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- Generous holiday allowance with the option to buy additional days
- Health screening, eye care vouchers and private medical benefits
- Wellbeing programs
- Life assurance
- Access to a competitive contributory pension scheme
- Long service awards
- Save As You Earn share option scheme
- Travel Season ticket loan
- Maternity, paternity and shared parental leave
- Access to emergency care for both the elderly and children
- RE CARES days, giving you time to support the charities and causes that matter to you
- Access to employee resource groups with dedicated time to volunteer
- Access to extensive learning and development resources
- Access to employee discounts via Perks at Work
About Us
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
If performed in NLD Amsterdam (Radarweg), the base pay range is €110,500 - €184,000. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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