Elsevier
Sr Product Mgr II
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Senior Product Manager II, Knowledge Management & AI
Do you have at least 8+ years of product management experience?
Do you have a wealth of experience with AI/ML products, especially generative AI, RAG, or agentic workflows?
Join us to shape how researchers build on their own knowledge with AI.
Location:
UK (London) or Amsterdam. Remote-first with periodic in-office collaboration.
About Our Team
We build LeapSpace, an AI-assisted workspace where researchers find scientific literature they can trust and do their best thinking in one place. We’re an international team and we work from evidence. The aim is simple: researchers should spend less time wrangling information and more time thinking. Own knowledge management and AI at LeapSpace, our AI-assisted research workspace: the product's memory of a researcher's projects, the personalisation around it, and how the AI reasons over the knowledge researchers bring with them and build up over time. The long-term ambition is a living, AI-maintained knowledge base for every researcher, evolving toward goal-oriented research the system can pursue iteratively. The role pairs strategy with delivery: you set that direction and ship it with your own squad, whose current focus is project spaces. We're looking for a Senior Product Manager with deep product judgment, hands-on experience with AI/ML products (generative AI, RAG, or agentic workflows), and the instinct to work from customer evidence alongside data science. UK (London) or Amsterdam; remote-first with periodic in-office collaboration.
About The Role
We're looking for a Senior Product Manager with deep product judgment to own the strategy for knowledge management and AI at LeapSpace.
This is a strategy-first role, but a pragmatic one. Researchers don't start from a blank page. They come with papers they've saved, drafts they've written, and questions they've chased for months. Your job is to make LeapSpace reason across that personal knowledge as well as the wider scientific corpus, and to turn today's scattered features into one experience that gets more useful the longer someone uses it.
The destination is ambitious. Think of a living knowledge base that the AI builds and maintains with the researcher: structured, current, and grown from every project, source, and finding they work through. From there the work points toward goal-oriented research, where a researcher states what they are trying to achieve and LeapSpace runs iterative research loops against that goal, drawing on everything it already knows about their work. You will define the staged path from today's features to that destination, and make each stage earn its keep.
The strategy ships through a real squad. You'll work in a team building project spaces: the workspace where a researcher's questions, documents, and findings live together, and the foundation the personal-knowledge experience grows from. You'll be in the detail with your engineers sprint by sprint. Beyond that, the near-term work is the product's memory of a researcher's projects, the personalisation around it, and the tools they use to keep and reuse what they find. It also covers how LeapSpace reads the documents a researcher brings in, though upload and storage themselves sit with a partner team you'll work with closely.
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You'll report and work alongside the Senior Director of Product Management and Strategy for LeapSpace. Day to day you'll work with a full-stack engineering team and an embedded data science team, and partner with the team that owns core retrieval. We want PMs who stay close to the technology and can reason about how the AI behaves, how it's evaluated, and where the trade-offs lie. You'll prototype with AI tools as you grow into that, but your craft is product management, not engineering.
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 knowledge management and AI. The near-term features are how that strategy shows up, not the strategy itself.
- Lead delivery of project spaces with your squad, and the wider current surface: the project memory system, the personalisation around it, and the tools researchers use to keep and reuse their work.
- Run rigorous customer discovery into how researchers actually manage and build on their knowledge, and turn it into product decisions you can defend.
- Use analytics and hypothesis-driven experimentation to make evidence the team's default way of deciding.
- Anticipate what the product roadmap will ask of the personal-knowledge layer (new project workflows, collaboration, richer integrations) and keep the strategy ahead of it.
- Partner with the team that owns document upload and storage on how LeapSpace surfaces and reasons over uploaded documents. Upload and storage functionality stays with that team.
- Partner with the team that owns core retrieval on how the AI reasons across a researcher's knowledge and the wider corpus.
- Work with embedded data scientists to evaluate response accuracy, relevance, and trust. Commission the evaluations, read the results, and turn them into prioritised improvements.
Requirements
- 8+ years of product management experience, with sustained tenure of at least three consecutive years at one employer. That depth is what builds real product judgment on hard, ambiguous problems.
- Demonstrated product judgment and strategic depth. You can frame a problem space, defend a trade-off under questioning, and articulate the user outcome, not just the feature list.
- Experience with AI/ML products, especially generative AI, RAG, or agentic workflows. This is central to the role.
- Proven delivery leadership within a squad: you keep a backlog healthy, sequence work well, and ship steadily in an agile environment. Comfort with ambiguity is essential; early-stage or startup product experience is highly desirable.
- Comfortable working with data science. You partner closely with data scientists, reason about evaluation and AI behaviour, and turn experimental results into product decisions.
- A user of knowledge management tools yourself: reference managers like Mendeley, Zotero, or EndNote, and research-organisation tools like Obsidian, Notion, or similar. You know first-hand how people collect, connect, and reuse what they know, and you have views on where these tools fail.
- Comfortable reasoning about architecture and technical trade-offs with a cross-disciplinary team, without writing production code. Hands-on prototyping with AI coding tools is a plus, not a requirement. It's something you'll grow into here.
- Strong customer-discovery instincts. You understand user pain points deeply and translate them into product decisions.
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If you are interested in the role, please apply with a cover letter and CV.
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 €100,400 - €167,300. This job may be subject to a collective labor agreement in the Netherlands. Please consult with the hiring team for further details.
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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