Product Manager

We're hiring a Product Manager to build Fibr's Agent Experience (AX) product with the founders, from zero to one.

The web was built for humans. AI agents are now reading, comparing and acting on websites on people's behalf, and most sites aren't built for them. Today companies meet this problem as "LLM visibility", AEO or GEO: why isn't my brand showing up in ChatGPT, Perplexity or Google's AI answers? That's the entry point. The bigger question is whether an AI agent can understand, evaluate, trust and act on a business. That's the product you'll build.
This is a whitespace role. There's no established playbook, no category leader to copy, and the platforms underneath change monthly. We want someone who can form a sharp point of view, test it fast, and turn what they learn into a product customers pay for.

The problem you'll work on
LLM visibility is an outcome. Agent Experience is the system underneath it. A brand can be mentioned by an LLM and still fail every step after that. We think about AX as five layers:

1. Visibility: can an agent find the business at all?
2. Understanding: can it work out what the product is, who it's for and how it differs, when key facts sit behind JavaScript, in PDFs or in images?
3. Evaluation: can it find pricing, specs, docs and proof to compare options?
4. Trust: is there enough evidence and consistency for the agent to recommend it?
5. Action: can the agent navigate the site and complete a task, like booking a demo, starting a trial or buying? Much of today's tooling focuses on layer 1, tracking mentions and citations. Your job is to decide where Fibr goes deeper, in what order, and how to prove it moves outcomes customers care about: discovery, qualified traffic and conversions from agents.

What you'll own
• The AX roadmap, with the founders. Decide what we build across the five layers, what we skip, and why. Defend the trade-offs with evidence.
• Customer discovery in a new category. Talk to marketers, growth leads, SEO teams and founders who are asking "why aren't we in ChatGPT?" Find out what they actually need, what they'll pay for, and what they're doing today instead.
• Experiments as a product input. Design and run tests on how ChatGPT, Claude, Gemini, Perplexity and Google's AI features read and act on real websites: server-rendered vs JavaScript-heavy pages, PDF vs HTML, structured vs unstructured product data, task completion by browsing agents. Turn findings into features.
• Defining what "good AX" means and how to measure it. Build the metrics and scoring that tell a customer where they stand and whether our product moved it, beyond mention counts.
• Specs and execution. Write clear PRDs and work daily with engineering, design and data science to ship. Make a messy problem feel simple to the people building it.
• Go-to-market alongside marketing and sales. Shape positioning, pricing inputs and launch narratives. Feed experiment findings into our content on LLM visibility, AEO, GEO and Agent Experience.
• Tracking the platforms. Follow announcements and documentation from OpenAI, Anthropic, Google, Microsoft and Perplexity, plus emerging standards for agents on the web. Work out what each change means for customers and for our roadmap, quickly.
• Outcomes after launch. Track what you ship, kill what doesn't work, and iterate toward user value and revenue.

What we're looking for
• 3–5 years in product management, ideally at an early-stage B2B SaaS company, with at least one product you took from idea to paying customers.
• Hands-on with AI. You use LLMs and agents daily and have opinions on where they fail. You understand at a working level how LLMs retrieve and cite sources, how AI search differs from classic search, and what browsing agents can and can't do today.
• Web fundamentals. You can explain rendering, crawling, structured data and schema, sitemaps and basic SEO without notes, and read HTML or a network log when you need to.
• An experimenter's mindset. You design tests with controls, separate signal from noise in non-deterministic systems, and say clearly what the data does and doesn't prove.
• Comfort with ambiguity. You've worked where the category, the buyer and the metrics were all undefined, and you made progress anyway.
• Sharp writing. Your PRDs are short and decisive, and you can explain a technical idea to a CMO and an engineer in the same meeting.
• Ownership and speed. You ship in weeks, not quarters, and you'd rather learn from a live experiment than a long deck.

Bonus points
• You've worked on SEO, AEO/GEO or LLM visibility tools, martech, CRO or website personalization.
• You've built with LLM APIs, browser agents or agent frameworks, even as a side project.
• You've sold to marketing or growth teams in the US.
• You write publicly about AI, search or the web.

Why Fibr
Fibr is building the future of the web: dynamic, autonomous and intelligent. Agent Experience is the next step of that mission. As AI agents become a new kind of website visitor, businesses need their sites to work for them too. You'd be the PM shaping that product from the start.
• Work directly with the founders on a new category, not a feature backlog.
• Competitive compensation and healthcare benefits.
• Significant ESOPs for early team members.
• Exposure to US markets and global product building.
• A collaborative, high-energy team that values ownership, bold thinking, hard work and fun.