Where we hire: We are both a remote-first and hybrid employer (depending on your role and location). We focus on building our team in the following geographic locations depending on the role.

United States - We're limited to hiring in the following states:

California, Colorado, Georgia, Massachusetts, Minnesota, New Hampshire
Washington

Canada - We're limited to hiring in the following provinces:

Ontario & British Colombia

Your next career:

Shopping is moving from search boxes to answer engines. Shoppers now ask ChatGPT, Perplexity, Gemini, and AI Overviews what to buy - and brands win or lose on whether AI represents their products accurately. This is a wide-open field with no established playbook, and fabric is defining it.

You'll own the research that helps define our AI Shopping roadmap. That means helping shape how we measure a brand's AI Shopping capability and how we optimize for the best outcomes. Your work becomes the research behind fabric's roadmap and the credibility behind our thought leadership.

This is a hybrid role by design - part researcher, part PM, part evangelist, part customer-facing. You'll design the studies, build the models, publish the findings, and sit with customers to show them what the data means for their business.

What you bring to the table:

• A demonstrated point of view on AI search (AEO/GEO). Whether you've worked hands-on with answer engine / generative engine optimization or studied AI search and digital markets rigorously, you can show what you've learned about how AI search actually behaves - from evidence, not just opinion.
• A rigorous quantitative foundation. Strong data science, statistical, and causal-inference / econometric skills, with fluency in Python, SQL, or similar. You can frame a question, design the analysis, build the model, and defend the methodology.
• Original research experience. You've run benchmarks, market studies, or performance studies - designing the question and the method, not just running standard reports.
• An SEO / search discovery background. You understand discovery from the inside and have grown into rigorous, data-driven measurement of it.
• Experimentation chops. You've designed and run A/B tests or similar to validate an idea and separate signal from noise.
• Storytelling with data. You can turn raw numbers into a clear narrative and a defensible point of view, and explain complex findings to non-technical audiences.
• Comfort with ambiguity. You can help build a measurement function from scratch, not just execute one someone else designed.
• Deep curiosity about commerce. Genuine interest in e-commerce, marketing, and analytics - you want to understand why shoppers and algorithms behave the way they do.

Nice to have

• External recognition for your research - press, whitepapers, published benchmarks, or conference talks.
• Customer-facing or consulting experience - you're comfortable presenting findings and recommendations directly to customers.
• Familiarity with the AEO/GEO tooling landscape and how brands currently try to measure AI visibility.
• Experience at an e-commerce, martech, or search company or working closely with retail brands and their product data.
• An advanced degree or academic research background in economics, digital markets, computational social science, or a related quantitative field.

The pay range for this role is:

136,000 - 182,000 USD per year (San Francisco)