AI Search Performance Lead (SEO + GEO/AEO) (SaaS / Remote)

Ready to own it, build it, and grow it?

The Mission

Publitas turns static, dead PDFs into interactive, shoppable digital content discovery experiences for global brands. Our customers rely on us to stay ahead of the digital curve, and our growth relies on dominating search visibility.

Why this role exists

We want to grow qualified leads to publitas.com through organic search and AI search — being the source that ChatGPT, Perplexity, Google AI Overviews, Gemini, and Claude cite when buyers research our space. This is an outcome-owning, build-capable role. You own the lead number, and you build the automation that scales it.

This is not a traditional content-writer or keyword-researcher role, and it is not a pure backend developer role. It's the rarer blend: someone who understands modern search performance end-to-end and can ship automation with Claude Code and LLM APIs.

Must-haves

• A demonstrable SEO result you owned end to end, with the conversion or lead outcome attached — not traffic alone.

• GEO/AEO capability: you've gotten content cited in AI answers and you know how to measure it.

• Hands-on builder: you ship automation using Claude Code, LLM APIs, and Python (or equivalent), not just describe it.

• Measurement-first: you instrument attribution before you scale, and you can explain how.

Nice-to-haves

• B2B SaaS, martech, or ecommerce-adjacent experience.

• Built competitive-monitoring or content workflows with LLMs and human review gates.

• Familiarity with GA4 and AI-citation tracking tools (e.g., Profound, Otterly, Ahrefs Brand Radar — examples, not requirements).

What you'll own

• Qualified lead growth to publitas.com from organic and AI-search channels — this is the metric you're measured on.

• SEO performance: technical health, rankings, and content quality on the pages that drive pipeline.

• GEO/AEO: getting Publitas cited in AI-generated answers for our category, and measuring citation share over time.

• Lead attribution from day one: instrumenting organic and AI-referred traffic through to qualified leads, so we can prove what's working rather than report traffic in isolation.

• The automation: designing and building the system that scales monitoring, content, and optimization. We have a hypothesis that much of this can run as an agent-based engine with human-in-the-loop review — you'll validate that, propose the architecture, and build what actually moves the lead number.

How you'll work (AI-first)

• AI-native execution: you use LLMs to work faster and to build systems, always behind human review gates — nothing auto-publishes unreviewed.

• You document and hand off what you build. We're not buying a black box only one person can run.

Engagement

This starts as a flexible-hours contract with a clear path to full-time. The first phase is a proof window: get attribution instrumented, ship the first automation, and show early movement in AI-search visibility and qualified-lead signals. Deliver against that and we convert the role to full-time. We commit when the results do.

At Publitas, we see AI as a core lever for performance, efficiency, and innovation. We expect all team members to actively use AI in their daily work to improve quality, speed, and output.

Depending on the role, this ranges from effectively using AI tools in day-to-day workflows to designing and scaling AI-driven systems. We are not looking for candidates who are “AI-curious”; we look for people who already use AI to do better work and can demonstrate tangible impact.