Join our team<br>

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PubX builds next-generation publisher-first agentic advertising infrastructure. Our AI makes real-time, revenue-critical pricing decisions for digital publishers. Our Bid Intelligence uses machine learning to optimize every programmatic ad auction individually, generating measurable revenue uplift for publishers. We’re currently ranked #5 globally in Prebid Analytics Adapter Rankings, and growing.

Join our team

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<div>Location: Remote (UK / EMEA)</div>
<div>Type: Full-time, permanent</div>
<div>Reports to: Product Lead</div>
<h1><br>About pubX</h1>
<div>pubX builds next-generation agentic advertising infrastructure. Our AI makes real-time, revenue-critical decisions for digital publishers and advertisers. We've priced over 1 trillion programmatic auctions, we're ranked #5 globally in the Prebid Analytics Adapter Rankings, and we're a founding member of AgenticAdvertising.org.</div>
<div>&nbsp;</div>
<h1>The Problem We're Solving</h1>
<div>Publishers and advertisers leave significant revenue on the table because ad sales are still largely manual, static, or rule-based. Every campaign is unique, but most campaign management systems lack the intelligence to evaluate context, demand, and deal potential in real time.</div>
<h1><br>Why This Role Exists</h1>
<div>We're building the infrastructure for agentic advertising: AI agents that sit on both sides of a media transaction, taking a buyer's brief through to a live, publisher-approved campaign with minimal manual work.</div>
<div>This role exists to take real ownership of a piece of that system. You'll take a defined area from discovery through delivery and iteration, with clear accountability for the roadmap decisions, the trade-offs, and whether it actually works once it's live.</div>
<h1><br>The Role</h1>
<div>You'll own a defined area of Agentic Advertising end-to-end: framing the problem, scoping the MVP, working directly with engineering to build it, and staying accountable for it once it's live. You'll be in the detail with engineering day-to-day.</div>
<div>This work is already running with real advertisers and publishers, and the standards underneath it are still being written. Cycles are short and what you ship reaches live campaigns quickly.</div>
<div>You'll work closely with the rest of the product team, engineering, and commercial teams.</div>
<h1><br>What You'll Do</h1>
<div>
<ul>
<li>Lead end-to-end discovery and delivery for your area of Agentic Advertising</li>
<li>Frame problems clearly and validate them through user research and data</li>
<li>Define MVP scope, success criteria, and iteration plans</li>
<li>Prioritise work based on impact, effort, and learning, and be explicit about what you're not doing</li>
<li>Work day-to-day with engineering to unblock delivery</li>
<li>Use AI to increase the speed and quality of your own discovery and delivery work, while holding a high bar for accuracy and data sensitivity</li>
<li>Support launches and adoption with Sales and Customer Success</li>
</ul>
</div>
<div>&nbsp;</div>
<h1>What Success Looks Like (First 6 Months)</h1>
<div>
<ul>
<li>At least one meaningful capability shipped end-to-end from discovery through launch, with instrumentation in place and at least one change made on the back of what it told you</li>
<li>A focused, outcome-driven roadmap for your area: priorities, trade-offs, and what you're deliberately not doing and the reasons why</li>
<li>Engineering trusts you to scope your area's work accurately</li>
<li>Strong working relationships across product, engineering, and commercial</li>
</ul>
</div>
<div>&nbsp;</div>
<h1>What We're Looking For</h1>
<h2>Must-have</h2>
<div>
<ul>
<li>5+ years product management experience shipping B2B SaaS products, where you defined the problems worth solving rather than delivering against a roadmap set elsewhere</li>
<li>Experience in AdTech / programmatic, ideally with exposure to the buy side, sell side, or both</li>
<li>Experience running discovery and scoping MVPs under real constraints, ideally without much supporting infrastructure (design, research, data) to lean on</li>
<li>Excellent written and verbal communication — able to make a case to technical and non-technical audiences without losing the nuance</li>
<li>Comfort using data to define and evaluate success, and knowing when the data doesn't answer the question</li>
<li>Pragmatic product judgment and a bias toward outcomes</li>
<li>A demonstrated habit of using AI to improve day-to-day product work</li>
</ul>
</div>
<div>&nbsp;</div>
<h2>Nice-to-have</h2>
<div>
<ul>
<li>Experience with technical products involving APIs, agents, or data integrations</li>
<li>Familiarity with agent protocols or agentic workflows (AdCP or similar)</li>
<li>Experience shipping AI-powered features or products</li>
</ul>
</div>
<div>&nbsp;</div>
<h1>How We Hire</h1>
<div>1. CV &amp; profile review<br>&nbsp;We look at relevant experience and background to confirm fit before moving forward.</div>
<div>2. Initial chat (45 mins)<br>&nbsp;A conversation about motivation, role fit, and a deeper dive into your experience.</div>
<div>3. Live task interview (60 mins)<br>&nbsp;A live exercise testing product thinking and problem-solving in practice, not just in theory.</div>
<div>4. Final interview (60 mins)<br>&nbsp;A behavioural interview covering how you think, how you work, your technical and commercial judgement, and whether we're the right fit for each other.</div>
<h1><br>Compensation &amp; Benefits</h1>
<div>Competitive salary, equity, and benefits. Leveling aligned with our product organisation framework.</div>
<div>&nbsp;</div>
</div></body></html>

<div>
<div>Location: Remote (UK / EMEA)</div>
<div>Type: Full-time, permanent</div>
<div>Reports to: Product Lead</div>
<h1>
<br>About pubX</h1>
<div>pubX builds next-generation agentic advertising infrastructure. Our AI makes real-time, revenue-critical decisions for digital publishers and advertisers. We've priced over 1 trillion programmatic auctions, we're ranked #5 globally in the Prebid Analytics Adapter Rankings, and we're a founding member of AgenticAdvertising.org.</div>
<div> </div>
<h1>The Problem We're Solving</h1>
<div>Publishers and advertisers leave significant revenue on the table because ad sales are still largely manual, static, or rule-based. Every campaign is unique, but most campaign management systems lack the intelligence to evaluate context, demand, and deal potential in real time.</div>
<h1>
<br>Why This Role Exists</h1>
<div>We're building the infrastructure for agentic advertising: AI agents that sit on both sides of a media transaction, taking a buyer's brief through to a live, publisher-approved campaign with minimal manual work.</div>
<div>This role exists to take real ownership of a piece of that system. You'll take a defined area from discovery through delivery and iteration, with clear accountability for the roadmap decisions, the trade-offs, and whether it actually works once it's live.</div>
<h1>
<br>The Role</h1>
<div>You'll own a defined area of Agentic Advertising end-to-end: framing the problem, scoping the MVP, working directly with engineering to build it, and staying accountable for it once it's live. You'll be in the detail with engineering day-to-day.</div>
<div>This work is already running with real advertisers and publishers, and the standards underneath it are still being written. Cycles are short and what you ship reaches live campaigns quickly.</div>
<div>You'll work closely with the rest of the product team, engineering, and commercial teams.</div>
<h1>
<br>What You'll Do</h1>
<div>
<ul>
<li>Lead end-to-end discovery and delivery for your area of Agentic Advertising</li>
<li>Frame problems clearly and validate them through user research and data</li>
<li>Define MVP scope, success criteria, and iteration plans</li>
<li>Prioritise work based on impact, effort, and learning, and be explicit about what you're not doing</li>
<li>Work day-to-day with engineering to unblock delivery</li>
<li>Use AI to increase the speed and quality of your own discovery and delivery work, while holding a high bar for accuracy and data sensitivity</li>
<li>Support launches and adoption with Sales and Customer Success</li>
</ul>
</div>
<div> </div>
<h1>What Success Looks Like (First 6 Months)</h1>
<div>
<ul>
<li>At least one meaningful capability shipped end-to-end from discovery through launch, with instrumentation in place and at least one change made on the back of what it told you</li>
<li>A focused, outcome-driven roadmap for your area: priorities, trade-offs, and what you're deliberately not doing and the reasons why</li>
<li>Engineering trusts you to scope your area's work accurately</li>
<li>Strong working relationships across product, engineering, and commercial</li>
</ul>
</div>
<div> </div>
<h1>What We're Looking For</h1>
<h2>Must-have</h2>
<div>
<ul>
<li>5+ years product management experience shipping B2B SaaS products, where you defined the problems worth solving rather than delivering against a roadmap set elsewhere</li>
<li>Experience in AdTech / programmatic, ideally with exposure to the buy side, sell side, or both</li>
<li>Experience running discovery and scoping MVPs under real constraints, ideally without much supporting infrastructure (design, research, data) to lean on</li>
<li>Excellent written and verbal communication — able to make a case to technical and non-technical audiences without losing the nuance</li>
<li>Comfort using data to define and evaluate success, and knowing when the data doesn't answer the question</li>
<li>Pragmatic product judgment and a bias toward outcomes</li>
<li>A demonstrated habit of using AI to improve day-to-day product work</li>
</ul>
</div>
<div> </div>
<h2>Nice-to-have</h2>
<div>
<ul>
<li>Experience with technical products involving APIs, agents, or data integrations</li>
<li>Familiarity with agent protocols or agentic workflows (AdCP or similar)</li>
<li>Experience shipping AI-powered features or products</li>
</ul>
</div>
<div> </div>
<h1>How We Hire</h1>
<div>1. CV &amp; profile review<br> We look at relevant experience and background to confirm fit before moving forward.</div>
<div>2. Initial chat (45 mins)<br> A conversation about motivation, role fit, and a deeper dive into your experience.</div>
<div>3. Live task interview (60 mins)<br> A live exercise testing product thinking and problem-solving in practice, not just in theory.</div>
<div>4. Final interview (60 mins)<br> A behavioural interview covering how you think, how you work, your technical and commercial judgement, and whether we're the right fit for each other.</div>
<h1>
<br>Compensation &amp; Benefits</h1>
<div>Competitive salary, equity, and benefits. Leveling aligned with our product organisation framework.</div>
<div> </div>
</div>