From $104K/yr
We are seeking a visionary Answer Engine Optimization Lead to spearhead our Large Language Model (LLM) and AI platform visibility strategy (e.g., ChatGPT, Claude, Google AI Overviews, Perplexity). Reporting into the Director of Marketing Acquisition, this role will be responsible for expanding our brand authority, maximizing developer mindshare, and driving new customer acquisition by optimizing MongoDB’s presence within LLM and answer engine responses. If you thrive at the intersection of technical content architecture, structured data, community advocacy, and AI-era discovery—and you want to lead a team on the front lines of defining the next wave of search experience optimization—this is a critical leadership role designed to accelerate target audience awareness and Product-Led Growth (PLG). This role will be based remotely in the United States. Key Responsibilities Define & Execute AEO Strategy: Design and own MongoDB’s global LLM visibility growth initiatives. Develop and execute strategies focused on increasing the citation share, sentiment, and accuracy of MongoDB across various technical developer audiences and agentic AI models Team Leadership: Oversee and scale a high-performing team of SEO, AEO, and content optimization professionals, fostering a culture of rapid experimentation in the AI search space Technical Information Architecture: Collaborate with Product, Engineering, and Documentation teams to optimize MongoDB’s digital footprint for LLM crawlers. Impose best practices for structured data, schema markup, knowledge graphs, and API/documentation accessibility to facilitate flawless RAG (Retrieval-Augmented Generation) ingestion UGC Response & Community Advocacy: Coordinate a multi-team framework (including Developer Relations and Support) to ensure timely, high-quality, and LLM-friendly insights are present on critical developer watering holes (e.g., Reddit, Stack Overflow, GitHub, Wikipedia). Leverage "build in public" tactics to organicall