Welcome!

WON redesigns how a business works: what its customers experience on the outside, and how its operation runs on the inside. We do that for retail and consumer brands, travel, hospitality, financial services, and private equity portfolios. We are not a consultancy that separates the thinking from the doing, and we are not a platform company with something to sell you. Those two halves are our two disciplines: Experience Intelligence and Operational Intelligence.

The firm is built around senior practitioners. The people you meet are the people doing the work, and the people who find the opportunity stay to design it, build it, and optimize it. AI gives exceptional people extraordinary leverage. It increases capacity; it does not replace judgment.

This role sits in Operational Intelligence, the discipline that gets inside the workflows running a business and rebuilds how they work. We sell a program, not a point solution. We come into a business across a defined set of areas, often led by customer experience, marketing operations, and forecasting and inventory, benchmark how the business performs in each, and use the gap against that benchmark to show where the opportunity actually is. Then we execute across those areas over the life of the engagement. Your accounts today are retail and consumer brands with potential to expand.

This role reports to the AI Practices Lead. You are the primary point of contact on your accounts and run them independently, with the Practices Lead joining when a conversation is notable or a decision calls for it.

What You’ll Own

• Your accounts end to end: you are the primary point of contact, you set the direction, and the AI Practices Lead steps in when a conversation is notable rather than as a matter of course
• Running the program rather than a point solution. Clients buy a long-term engagement across our areas, not the one tool they got excited about, and expansion comes from delivering, reassessing what the business needs, and moving into the next area
• Discovery led by those areas rather than by whatever the client raises first: benchmark how the business performs in each, and stay embedded through recurring touchpoints and their internal channels so you see the opportunity before they package it for you
• The business case behind everything you scope: what it should move, by how much, what it costs us to deliver, and how we will know
• Specifications precise enough for a specialist engineer or analyst to deliver against, direction of that delivery across concurrent projects, and adoption once it lands, because a system nobody uses is indistinguishable from a system nobody built
• Quality and profitability on your accounts, and what becomes repeatable: which parts of a solution turn into a defined offering with known effort and margin, and which stay bespoke

How Success Is Measured

• Clients buy the program rather than the one tool they got excited about, and treat you as an operational and AI partner instead of a vendor contact
• Work expands past the project that opened the account, because you found the next thing before the client thought to ask
• Contractors execute from your direction without a second discovery pass or a rewrite of the spec
• What you scope moves a number the business already tracks, and stays in use after launch
• Several accounts run at once without quality, client trust, or margin slipping, and the AI Practices Lead is no longer the default path for discovery and scoping

What You’ll Bring

• Startup experience, built or operated, and real comfort creating the playbook while delivering the work
• Client-facing experience with the maturity to lead an executive conversation, tell a client something they are paying not to hear, and pull the conversation back to the business problem when they jump straight to the tactical
• Deeply AI-native rather than a casual user, with AI-enabled tools, products, custom agents, or workflows you have actually built. The bar is materially above vibe coding, and we will ask you to demo and walk us through an Applied AI case study project
• Enough technical and analytical fluency to reason through agent systems, data connections, backend architectures, APIs, and implementation tradeoffs, even though you will not be the primary engineer. SQL/Python experience is valuable
• You can read a P&L, explain how a Shopify or e-commerce business actually makes money, and build financial models

Bonus points: time inside a consumer or e-commerce brand on the operator side; published writing or talks on applied AI

How We Work

• We don’t start by asking where AI can be deployed. We start with where value is being left in the business, and we build systems that make the business healthier rather than tools that make one team’s day slightly nicer
• Insight has to become a shipped system. We work inside our clients’ businesses, not adjacent to them, and strategy that stops at the recommendation is half a job
• You own the whole arc: the relationship, the discovery, the business case, the direction of delivery, and the number at the end, with specialists on tap so your scope is not capped by what you can personally build
• An early hire into the practice, so you shape the offering rather than inherit one, and saying no is part of that. A client asking for the wrong thing is a conversation, not an order
• Probably not the right environment if you want a fixed scope, a predictable week, or distance from the outcome

If you want to write the recommendation and hand it off, this probably isn’t for you. If you want to own the client, find the thing that is actually broken in their business, direct the people who fix it, and be held accountable for whether anything changed, we’d love to meet you.