Remote Product Management Jobs in London, UK

You’re a product exec who still ships. You can take a fixed product vision, slice it into the smallest valuable increments, and get enterprise-grade AI capabilities into production fast without turning the work into roadmap theater. You’ve already lived through the “AI will solve everything” phase, you know where it breaks, and you’re good at building anyway. If your best work happens when you own the outcome end-to-end (i.e., deciding, prototyping, hardening, launching, and watching real customers use it), then keep reading.

Most of the software industry is doing AI like a costume change: sprinkle a chatbot on top, announce a “copilot,” call it innovation, and hope buyers don’t ask hard questions. We’re doing the opposite. We’re building AI-native capabilities that earn their place in the product by delivering measurable enterprise value, and we’re doing it at a speed that makes traditional planning cycles look like self-harm. Our edge is compressing Sell → Design → Build loops, ruthless scope control inside an established direction, and production deployments that meet enterprise standards without months of coordination overhead.

The core of this job is rapid delivery of enterprise-grade, AI-native product capabilities into customer hands. It is personally prototyping with modern AI tooling to validate feasibility before engineering hardens the build. It is owning delivery from vision refinement to production deployment, making decisive tradeoffs, and shipping inside a fixed frame. It isn’t “adding AI features” without a clear value proposition. It isn’t a feature-request intake queue, a PRD factory, or a slide-deck career. It isn’t vague vision statements, model metrics detached from user reality, or optimism that assumes AI works perfectly.

You’ll sit close to engineering and operate as a player-coach: part builder, part decision-maker, zero part coordinator. You’ll translate an established vision into executable scope, prototype quickly to collapse ambiguity, and drive releases that customers can actually adopt in real enterprise environments. If you’ve shipped net-new enterprise software, used AI as an execution layer, and you’re calm when the hype collides with production constraints, you’ll have the autonomy to move fast and the responsibility to make it hold up. If that sounds like relief instead of pressure, please apply.