Product Manager, Squad Lead

🕒 il y a 3 mois

🇬🇧 Royaume-Uni – Télétravail

⏰ Temps Plein

🟠 Senior

✅ Responsable Produit

👻 Score fantôme 58%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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nPlan

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2017

🤖 Intelligence artificielle

🏗️ Construction

☁️ SaaS

🔥 Financement dans la dernière année

💰 €16 000 000 Series B - nPlan en 2025-10

Artificial Intelligence • Construction • SaaS

nPlan est une entreprise de logiciels axée sur l'IA qui applique l'apprentissage automatique au contrôle et à la livraison des projets pour les projets d'investissement. Formée sur un ensemble de données propriétaires comprenant 750 000 plannings historiques représentant plus de 2 000 milliards de dollars de dépenses de construction, nPlan fournit des outils de prévision, de quantification des risques et de décision intelligente qui s'intègrent aux plannings existants pour aider les équipes à identifier et gérer les risques, améliorer les prévisions et protéger les projets contre les retards et les dépassements de coûts. Sa suite de produits comprend des solutions de prévision de portefeuille et de projet unique (Insights Pro/Core/Risk Professional), Schedule Studio pour la génération et l'édition de plannings, AutoReport et un Vérificateur d'Intégrité de Planification. Les clients de nPlan incluent des propriétaires-exploitants, des entrepreneurs généraux, des consultants et des PMO dans des secteurs tels que les autoroutes, le ferroviaire, les services publics, l'énergie, les bâtiments commerciaux et publics.

Description

• Own your squads' quarter: plan it, reconcile it against unplanned work and support demands, and deliver it. • Make build/kill decisions on evidence, and know what value a piece of work will create — and how you'll measure it — before you build it. • Build, not just brief: write clear specs, prompt agents effectively, and review and edit generated code and output rather than writing from scratch or handing over. • Keep idea-to-test in days by choosing the cheapest path to a valid test. • If you haven't touched an AI coding tool today, something's wrong. • Design and ship AI agents: decide what an agent should do, what it must never do, and where the human stays in the loop. • Shape the context, tools, and guardrails it works with, and own the trade-offs between model choice, prompting, retrieval, and UX. • Run evals — this is central to what we do: define what good looks like before you build, then prove it with structured evaluations — representative datasets, scoring rubrics, and success metrics covering quality, cost, and reliability. • An agent that demos well but doesn't improve real outcomes doesn't ship. • Kill things fast when the evidence says so; we measure ourselves in outcomes shipped and experiments correctly killed. • Help people decide under uncertainty: our products exist to help people act when the future isn't certain. • You'll shape how we turn risk and forecasts into something a busy executive can make a confident call on. • Get close to customers: run user and buyer research, sit in on client and sales meetings, and treat real customer feedback as your most valuable input. • Lead contributors, not a process: lead your squad to decisions and delivery with no handovers, coordinate dependencies with other squads, and spread what your squad learns through our guilds.

🎯 Exigences

• Two-plus years owning a B2B or enterprise AI or SaaS product — accountable for a product area, not tickets — with shipped, adopted features that real clients depend on. • You already build with AI, daily: prototypes, analysis, working code you review and edit rather than write from scratch. • You can go from idea to a working test without an engineer as intermediary. • You've built with LLMs in earnest — enough to reason about model choice, prompting, context and retrieval, and tool use, and to know that an eval suite is what separates a good agent from a lucky demo. • You can take an ambiguous problem, get to the heart of what customers actually need, and make the right calls — because you understand the trade-offs, not because you followed a framework. • You've killed things. You can point to experiments you ran, what they told you, and the roadmap items that died as a result. • You're fluent with data: you use it to find the problem worth solving and to know whether what you shipped actually worked — including designing structured evaluations, not just reading dashboards. • You communicate sharply: you can make a complex trade-off legible to an engineer, a customer, and a member of the leadership team in the same afternoon. • The problems are hard, the stakes are real, and the path isn't always clear — you're energised by that, not slowed down by it.

🏖️ Avantages

• 30 days paid vacation • Flexible working hours • Breakfast at work • Regular social & team events

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