nPlan
Hiring now
Remote · United KingdomPosted 3 months ago
nPlan
ApplyShape how the world's biggest infrastructure gets built — HS2, Heathrow, Sizewell C and more, where the decisions your product informs are measured in years and billions.†
Build on world-class AI — the most accurate construction risk forecasting on the market, from a MacRobert Prize–finalist engineering and research team.
Lead, and build, for real — run your own squad, plan its quarter, ship with your own hands (and your agents'), and take on more scope as fast as you can earn it.
nPlan has built a unique AI platform that turns the data behind major construction projects into decisions their leaders can act on — forecasting delay and cost risk on some of the world's most important infrastructure, and helping the people running those projects decide what to do about it. Behind that is a machine learning capability that forecasts project risk more accurately than anything else on the market — trained on one of the largest datasets of construction schedules in existence, and built by a world-class engineering and research team recognised as a MacRobert Prize finalist, the UK's top engineering award.
As a PM here, that's what you get to build on — and the team you get to build alongside.
We don't run product management the way most companies do. AI has collapsed the cost of building software, so we've rebuilt how we work around a simple idea: when execution is cheap, judgment is the scarce resource.
We organise into squads of 2–3 people, and everyone in a squad is a contributor. There is no "write the spec and wait," no design-and-handover. As a Product Manager at nPlan, you lead one or more of these squads. You're accountable for planning your squad's quarter: you own the mission, reconcile priorities when unplanned work lands, and have genuine authority to make trade-offs — including saying "not this quarter." And you build. You'll prototype with AI tools, direct agents, review and edit generated code, and take ideas to working tests in days, not weeks.
Increasingly, the product itself is agents. Our direction is to move from tools that help people run projects to the AI that runs the project — agents that read what's happening on a programme, work out what matters, propose actions, and eventually act, with humans signing off rather than doing the legwork. You'll design these agents: what they do, what they must never do, and where the human stays in the loop when the consequences are measured in years and billions.
And because you can't ship an agent you can't measure, evals sit at the centre of how we work. Nothing counts as done until a structured evaluation shows it's actually good.
Squads don't own permanent territories. They have themes they align with, and each quarter they take on missions based on what nPlan needs most and what the squad is best equipped to deliver. The through-line across everything we build stays the same: helping the people who run major projects make better decisions when the stakes are high and the future is uncertain.
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. Our clients run multi-billion-dollar projects and carry real accountability for them; understanding their world is the job.
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.
Please mention the word 'crane' in your application.
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.
Experience with a product built on data science or machine learning, and comfort talking about forecasting, uncertainty, and probabilities.
Experience selling or shipping to senior operational or finance buyers (the people accountable for large, complex programmes of work).
Some understanding of the construction industry, planning, and/or risk.
A formal technical background (development, engineering, or data).
We are still a relatively small team, so there is plenty of opportunity for a high degree of ownership and growth over different areas of the product, and you will be directly exposed to all areas of the business.
Meaningful equity — you're taking on real ownership, and we want you to share in what you help build.
🏄 Generous paid holiday, because time with the people and things you care about matters.
🕐 Flexible working hours and a flexible remote setup — into the Shoreditch office just 1–2 times per month (or as often as you'd like), plus quarterly company get-togethers.
🥯 Regular lunches, socials and opportunities to connect as a team.
A Learning & Development budget, strong Health & Wellbeing support, and generous family leave.
Your voice will always be heard. What you do or say counts, not who you are or where you're from. We are a cross-disciplinary team, and come from all backgrounds and cultures.
We have three core values that underlie everything we do:
Learn from Everything
Be Radically Truthful
Aim High, Run Fast
These enable us to create a collaborative, inclusive environment where we can move effectively and efficiently to implement the best solutions.
We are working hard to create a workplace that is inclusive to everyone, no matter their background, or where they are in life. We believe that only a truly diverse place can create great products that serve a wide audience and improve the world.
We believe in equality of opportunities and that's why we make sure that these ideas are reflected in our values, and that we really apply these in all aspects of our company culture.
If you have a need for any adjustments during our interview process, let us know and we will do our best to accommodate them.
Intro call (Product team member) (15 min)
Skill set interview (Product Lead) (30 min)
Practical exercise: prototype something with AI tools and show us how you'd eval it (Product Lead & squad member) (60 min)
Values Alignment call (60 min)
On-site (half a day, can be remote)
If this sounds like you, we'd love to hear from you!