AI Product Manager – £130-160k + bonus + equity – Biotech/Health Data Software Platform – Remote (London preferably, or US East Coast, or parts of Europe)
Introduction
Our client is a profitable, venture-backed health data and AI company. Its federated platform allows analysis to run inside the environment of the data custodian, so that the world’s most sensitive patient data can be used for research without ever leaving its source. It works with national precision medicine programmes, major commercial data providers and global pharma, and has raised around $70m.
It is now launching a new AI product for life sciences research — think a genuinely advanced research agent for scientists, brought to market product-led rather than through enterprise sales. It is being built by a small, independent team whose only job is this product. You would own it end to end as a player-coach: setting strategy, building hands-on with engineering, and hiring the team around you. Launch is targeted for early Q1, so this is a build-now role rather than a plan-now role.
Location
Remote-first. London is the preferred centre of gravity, but the client is following the talent and will consider the US East Coast and European time zones. They intend to open an office where the team concentrates — weekly together if co-located, roughly monthly if not.
Key Role Details
- Own product strategy and roadmap for a new AI product line, end to end.
- Build the product hands-on with the engineering team, from discovery through shipping and iteration. Much of the underlying platform exists and can be reused as microservices; the AI orchestration, tool calling, context handling, memory and the full user journey are still to be built.
- Own product marketing — positioning, messaging and launch execution.
- Translate the needs of scientific users into product decisions, working directly with researchers in pharma and academia.
- Hire exceptional people into the product organisation as the unit scales.
- Report directly to the CEO on product progress and adoption.
- The initial user base is researchers working on target identification and validation, biomarker discovery and drug–target chemistry — the pre-clinical R&D effort.
Experience and Competencies Required
- Five to fifteen years of product experience.
- A biomedical background — biology, computational biology, genetics or a related discipline. This is a firm requirement: you should understand the science at the level of a working scientist and be able to engage credibly with biomedical and genetic researchers.
- You have shipped analysis tooling for early-stage R&D to a biomedical scientist user base, and it was genuinely adopted. This can be open source or commercial — the client cares more about the similarity of the use case and the evidence of adoption than about whether it was sold.
- Deep familiarity with AI/ML product development and the current LLM ecosystem.
- A track record of working directly with engineering teams to build and ship, not only to specify.
- Strong product marketing instincts, and the ability to position technical products for enterprise buyers.
- Comfort operating as a player-coach in a small, independent team with an aggressive launch timeline.
Tooling built purely for internal use inside a single organisation will be considered, but the client is clear that evidence of voluntary adoption by a wide user base is what they are really looking for.
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