Answer Engine Optimization (AEO) Lead

About this role

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 organically feed LLM training datasets with high-authority brand mentions

• Evangelize AI-First Content Frameworks: Create corporate guidelines and train cross-functional SMEs, technical writers, and marketers to write effectively for LLMs (e.g., token-friendly syntax, clear entity relationships, and direct intent fulfillment)

• Advanced Analytics & Attribution: Partner with Data Science and Analytics teams to pioneer new framework metrics for AEO, including Share of Model (SoM), LLM citation impact across third-party sites, and AEO contribution to PLG sign-ups and pipeline

Qualifications

• Experience: 8+ years of experience in technical SEO, digital strategy, technical content marketing, or growth engineering, with at least 2–3 years specifically focused on emerging AI technologies, LLM optimization, or semantic search. At least 3 years of experience leading an SEO team

• Leadership: Proven track record of hiring, leading, and mentoring technical marketing professionals, alongside a demonstrated ability to influence matrixed cross-functional teams (Product, DevRel, Engineering) without direct authority

• Technical Acumen: Deep understanding of how LLMs crawl, index, and retrieve information. Familiarity with semantic HTML, JSON-LD, knowledge graphs, and how modern search engines leverage vector spaces and RAG

• Developer Empathy: A strong grasp of how software engineers, architects, and technical decision-makers discover products. You understand the cultural nuances required for authentic, high-value engagement in developer communities

• Executive Communication: Exceptional ability to translate complex AI/SEO technicalities into clear, high-level business outcomes and ROI for executive leadership

• Tooling Toolkit: Proficiency with enterprise SEO suites (e.g., Conductor, Ahref, SEMrush), modern AEO/LLM monitoring platforms (e.g., Profound), web analytics (Google Analytics/Amplitude), and project management software (Jira)

Preferred Qualifications

• Experience with developer community and social listening tools (e.g., CommonRoom, Sprinklr, Reddit Mod Tools)

• Background in technical writing or managing technical content pipelines for developer tools, databases, or cloud infrastructure

• Basic understanding of Python or SQL to assist in scraping, analyzing LLM outputs, or manipulating large datasets

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the data platform for the AI era, enabling builders to create, transform, and disrupt industries with software. MongoDB’s unified data platform, the most widely available, globally distributed data platform on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 67,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB.

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy , we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB , and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recrui

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