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AI and data

AI Visibility Analyst

Kyiv / Remote-EUFull-time

Monitors client brand presence across ChatGPT, Gemini, Perplexity and Google AI Overviews; builds source-recovery and source-strengthening plans tied to Wikipedia / Wikidata work.

What you'd own

  • Run weekly visibility scans across the LLM stack and build per-client visibility deltas — what shifted, why we think it shifted, what we'd do about it.
  • Map the citation sources the AI engines actually pull from for the client's industry — sometimes Wikipedia, sometimes Wikidata, sometimes neither.
  • Build source-recovery plans when a client's brand mention drops or gets attributed to the wrong entity.
  • Coordinate with the editorial team on which Wikipedia / Wikidata edits would actually move LLM visibility — and which won't.
  • Stay current on retrieval and training-data architecture changes at the major LLM vendors — this market changes in weeks.

You'll thrive here if

  • You're fluent in retrieval-augmented generation as it exists in production at OpenAI / Anthropic / Google scale — at least at the level of being able to read the papers.
  • You're sceptical of vendor 'AI SEO' claims and can explain why most of them are wrong.
  • You can build a dashboard in something other than a vendor tool when needed.
  • You write reports a non-technical client will understand.

The first weeks

Onboarding pairs you with the Head of Digital for the first month — you'll learn the in-house monitoring stack (we built our own; vendor tools weren't honest enough) and read the past 12 weeks of client visibility reports. Escalation: founder for client-facing recommendations, Head of Digital for tooling questions. You'll publish a weekly internal note on what shifted across the LLM stack — this becomes a team artefact.

Apply: one email instead of a portal and forms

We reply to every application. Put the role and your name in the subject line.

team@wikibusines.com · Application — AI Visibility Analyst — [your name]Write an email

What to include

  • CV, preferably as a PDF
  • Your LinkedIn URL
  • Your Wikipedia username and the language editions you edit
  • A paragraph of 6–8 sentences on what brought you to this work