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Scarlet is a medical technology company that combines clinical, technical, and regulatory expertise with AI agents and software to accelerate certification of medical devices. The company helps ambitious technology companies cut a year or more from certification timelines for AI-enabled medical devices and shorten product-update cycles from months to weeks.
As a Product Manager, you will own a meaningful product area end to end. You will develop deep understanding of the people and problems within your domain, set clear direction, decide what matters most, and work with product design and engineering to deliver measurable improvements.
You will sit close to regulatory experts, account managers, and customers in the London office. Their expertise will provide rich signals, but not a ready-made roadmap. Your job is to turn those signals into coherent product strategy, make trade-offs openly, and ensure what you build improves both the quality and speed of certification.
Key responsibilities include: owning strategy, roadmap, and outcomes for a product area from discovery through launch, adoption, and iteration; partnering closely with product design, engineering, and regulatory experts to translate complex requirements into clear, trustworthy workflows; spending time with customers and internal users to understand their work and distinguish underlying problems from requested features; prioritizing across customer value, regulatory rigor, operational efficiency, technical constraints, and company goals; keeping the team aligned on problems, intended outcomes, and decision trade-offs; communicating product direction, decisions, progress, and learning across the organization; and helping improve Scarlet's product management practices as the team grows.
You will have substantial autonomy and be trusted to form a point of view, test it against evidence, and change course when evidence changes.
REQUIREMENTS:
- Evidence of owning and shipping complex products from discovery through delivery and iteration
- Strong product judgment, including examples of difficult prioritization choices made under real constraints
- Technical fluency to work effectively with engineers on systems, data, APIs, and trade-offs of AI-enabled products
- Clear, precise written and verbal communication, including ability to explain complex decisions to different audiences
- Comfort working in ambiguity, taking responsibility, and updating your view when new evidence appears
- High standards for product quality, reliability, and trust
PREFERRED QUALIFICATIONS:
- Experience in health technology, enterprise software, vertical SaaS, or another regulated industry
- Experience building products for complex, multi-stakeholder, or expert-led workflows
- Experience with AI-enabled products, including evaluation, failure modes, and appropriate guardrails
- Experience in an early-stage or fast-growing company where product practices were still being formed
