Make is the platform to manage all your automations and AI agents in one visual landscape – for teams driving business impact without relying on developers. Part of Celonis, a general leader in process intelligence recognized on the Forbes Cloud 100 for seven consecutive years, we're headquartered in Prague, Czechia, with hubs in Madrid, Munich, Raleigh, and Pristina, and teams across the UK, France, India, and the Netherlands, among other locations.
You’ll build the strategy, systems, monitoring, and content mechanics yourself, and prove out what generative visibility is worth to a workflow-automation and AI-agent platform. Traditional organic SEO stays part of the job, but it's the floor, not the ceiling.
What you'll own
GEO / AEO strategy build and run Make's approach to being cited (correctly, favorably, and often) across ChatGPT, Perplexity, Google AI Overviews, and Claude.
Citation monitoring stand up prompt-level tracking of where Make shows up, where it doesn't, and where competitors are winning the citation instead.




Authority & source repair identify and close the gaps in the sources LLMs actually draw from (this includes unglamorous work like earning back reinstated, high-trust reference sources).
Entity-based content architecture work with the content team to restructure key topics into the clusters and schema that both traditional crawlers and LLM retrieval reward.
Technical SEO own Core Web Vitals, indexation, structured data, and site health well enough that it's never the reason organic underperforms.
Automated tooling build lightweight automation (scripts, LLM APIs) to scale audits, competitive tracking, and reporting monthly.
Insight to action translate visibility data into a short list of things the business should actually do differently, not a dashboard nobody reads.
What you bring
5+ years in SEO, with the last 1–2 spent seriously engaging with how generative/AI search actually works: not just aware of GEO, but already testing it.
Comfortable bei

📌 Senior GEO Manager (Madrid)
🏢 Make
📍 Madrid