Set up and track LLM visibility for our brokerage partners: Defining how a brand’s presence in AI answers gets measured (mentions, sentiment, competitive positioning) and monitoring it consistently over time.
Analyze the data to find the story: Where a partner shows up, where they don’t, which competitors own which angles, and what’s actually moving the needle.
Report to partners in a way that’s clear and high-value: Translating visibility metrics into concrete recommendations.
Push visibility higher: Identify the angles where each broker is genuinely strong, and shape how those strengths get expressed in content so the AI models pick them up and surface them.
Own the client relationship across the project lifecycle: from deal scoping through to recurring reporting and visibility growth.
Drive Product Development: take part in building up products that help retail investors through their investment journey.
Leverage New Tools: use advanced tools like Python, Ahrefs, and Google Search Console to optimize research and content strategies.
Hands-On Testing: evaluate global brokerage platforms, including order execution, fees, and trading tools.
Requirements
Strong analytical skills and comfort working with data: pulling it, interrogating it, and drawing conclusions you can defend.
Clear communication in English, written and verbal, who can present findings to external partners with confidence.
Experience in managing complex projects and making high-stakes decisions.
Demonstrated ability to work independently and represent professional interests in an all-staff meeting; Commercial awareness, comfortable in client-facing and negotiation settings, not just behind the data.
A genuine interest in how AI search and LLMs work, and how brands earn visibility within them.
Familiarity with SEO and search visibility tooling (Ahrefs, GSC, etc.).
Working knowledge of SQL or comfort with BI tools (BigQuery, Metabase, etc.).
Proficient in Excel and Google Workspace.
Interest and understanding in the brokerage, fintech, or broader financial services space.
Nice to have: 2+ or more years of experience in investment management, brokerage, or related industry.
Deep knowledge and real experience in capital markets.
Creative problem solver with fresh content/analysis ideas.
Tech Stack
BigQuery
Python
SQL
Benefits
A unique opportunity: to pioneer a new AI specialization and become an expert in one of the fastest-growing areas of search.
Remote First: Work primarily from home, with weekly office visits if you live in Budapest.
Full-time office option available.
Flexible Working Hours: Adjust your work schedule as needed.
Competitive Salary: We provide and follow market-based benchmarks for your salary with yearly adjustments.
Bonus and Equity option: Benefit from a bonus system that rewards outstanding contributions, and there is an option to receive equity.
Swiss Knife Knowledge: Gain knowledge in data analysis, SEO, AI visibility, product development, investing/trading, and many more.
Feedback & Transparency: Transparent and advanced feedback with monthly performance discussions.