Senior Product Manager in London

Wholesale is a $50 trillion market still working the way it did in 1950. 90% of transactions happen offline, over calls, catalogues and trade shows, and a product passes through four or five layers of distributors and wholesalers before it reaches a store, with every party deciding on a fraction of the picture. By the time it hits the shelf, it costs roughly 40% more than the maker charged. That inefficiency tax runs into the trillions, and everyone pays it every time they buy anything.

Qogita is building the operating system that replaces that chain, which makes the product the core of what we are building. Every job of the traditional supply chain gets done once rather than at every layer, by a self-learning system rather than by hand: a buyer who used to deal with twenty suppliers gets an instant basket assembled from every available seller, forecasting reads what is actually selling in every market as it sells, and goods move straight from seller to retailer on the cheapest and fastest route. No part of it stands alone. The order book, the demand planner and the logistics network are each worth more combined with the others, every layer has to be machine-readable and actionable by agents as well as people, and every transaction writes a record that sharpens the next price, allocation and route. Deciding what to build, in what order, and which steps to skip entirely is the product problem, and it is already working: 95% of transactions involve no human touch, AI agents resolve over 90% of unique issues with zero human intervention, and the business is doubling every year.

The role

Most European wholesale still runs on PDF price lists, WhatsApp threads and payment terms designed to squeeze whoever has the least cash. Nobody designed that. It accumulated, and it's still how most of a very large industry works.

We're hiring one Senior Product Manager to own a hard part of replacing it. You'll take a single surface end to end: what gets built, why, and whether the number moved afterwards. There is no roadmap waiting for you and nobody is going to write your specs.

Depending on your strengths, that surface is likely to be one of the following:

• The autonomous procurement layer: agents that watch price movements across thousands of supplier feeds, forecast demand, raise purchase orders and handle routine supplier email. Most of the straightforward operational work is already automated. The open question is the rest of it, and what has to be true about accuracy and auditability before software is allowed to commit company money.
• Price and supply intelligence: we can see pricing, availability and demand across this market in a way no individual participant can. Whether that stays an internal tool or becomes something brands and large buyers pay for is genuinely undecided.
• Catalogue and trust: matching, deduplication, authenticity and supplier reliability scoring across hundreds of thousands of SKUs. Nobody will congratulate you for it, and everything else depends on it.
• Buyer economics: financing, terms, replenishment and retention. The levers that decide whether an independent retailer is still trading in five years.

• Own the strategy, the specs and the outcome for your area, and be the person accountable when the metric doesn't move
• Work from what's economically and physically true: units, margins, lead times, cash cycles, failure rates. "That's how marketplaces do it" isn't an argument here. A lot of industry convention is old error nobody went back and re-examined
• Try to delete the thing before you build it. Every screen, field and integration is something a person maintains for years. Removing ten workflows is usually worth more than shipping an eleventh
• Question whether a process should exist before you automate it, otherwise you get the same waste faster and buried in code
• Do your own analysis. The warehouse is open and you won't be queuing behind an analyst to find out whether your idea worked
• Bring the number, the sample size and the reason you might be wrong. Changing your mind publicly when the data turns against you counts in your favour here
• Go and look at the actual thing: sit with ops, listen to supplier calls, read the orders that failed. Judgement built only from dashboards decays quickly
• Work directly with engineers, designers, data scientists and the commercial teams, in the room, at pace. We ship weekly and make reversible decisions in hours