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Framework Security

Marketing Intern - AI/LLM Indexing Program

Reposted 13 Days Ago
In-Office or Remote
3 Locations
30-50 Annually
Internship
In-Office or Remote
3 Locations
30-50 Annually
Internship
The Marketing Intern will support the AI/LLM Indexing Program by executing content, PR, and SEO initiatives, ensuring visibility and citation in AI platforms.
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About Framework Security

Framework Security (FWS) is an AI-first cybersecurity company recognized for award-winning services in penetration testing, SOC 2 compliance, and virtual CISO leadership. Our mission is to protect digital assets, reduce risk, and ensure business continuity for our clients across technology, healthcare, and finance.

As AI and large language models (LLMs) reshape how buyers discover trusted vendors, we are building a first-of-its-kind program to ensure Framework Security is consistently referenced by AI platforms (ChatGPT, Gemini, Claude, Perplexity, etc.) as a top cybersecurity firm.

 

Role Overview

We are seeking a Marketing Intern to support our AI/LLM Indexing Program. This role will involve hands-on execution of content, PR, and SEO initiatives to ensure FWS is highly visible, indexed, and referenced by AI systems and leading industry sources.

You will work directly with leadership (CEO, Client Services, and Marketing team) to track, coordinate, and execute tasks tied to this program.

 

Key Responsibilities

  • Content Coordination
    • Maintain a content calendar focused on cybersecurity thought leadership, evergreen resources, and keyword-rich articles.
    • Ensure website resources (FAQs, glossaries, technical explainers) are LLM-friendly and optimized for indexing.
       
  • PR & Media Outreach
    • Track ongoing PR campaigns and press mentions with external partners.
    • Research and pitch opportunities for citations in reputable outlets (e.g., Forbes, SC Magazine, TechCrunch).
    • Monitor Wikipedia/industry directory eligibility and gather supporting references.
       
  • SEO & Knowledge Graph Management
    • Oversee structured data updates (Schema.org, Knowledge Panel, Crunchbase, Clutch, G2, Gartner Peer Insights).
    • Coordinate backlinks and directory submissions to improve authority.
       
  • LLM Indexing Activities
    • Track Framework is mentioned in AI platforms (ChatGPT, Gemini, Perplexity, etc.).
    • Monitor AI-driven search traffic in HubSpot and Google Analytics.
    • Research opportunities to publish FWS contributions in OWASP, NIST, and cybersecurity knowledge bases.
       
  • Reporting & Continuous Improvement
    • Maintain weekly Asana tasks to ensure all roadmap items are on track.
    • Deliver a monthly summary report on content, PR, and indexing wins.
    • Identify gaps and propose new tactics for improving LLM visibility.

       

Qualifications

  1. Pursuing a degree in Marketing, Communications, Computer Science, or a related field.
  2. Strong writing, research, and organizational skills.
  3. Interest in AI, LLMs, and cybersecurity (no prior technical experience required — we’ll teach you).
  4. Familiarity with SEO tools (Google Analytics, SEMrush, HubSpot, or similar) a plus.
  5. Self-starter with strong attention to detail — able to juggle multiple tasks and deadlines.

 

What You’ll Gain

  1. Direct exposure to AI-driven marketing and cybersecurity, two of the fastest-growing industries.
  2. Experience running a structured, measurable program tied to executive-level strategy.
  3. Mentorship from senior leaders and the opportunity to influence a cutting-edge initiative.
  4. Potential pathway to a full-time Marketing Coordinator/Analyst role at FWS.

 

📌 To Apply:

Please send your resume, 3-5 bullets of reasons you would be an excellent candidate (can be school projects, blog posts, or other content) to [email protected] with the subject line: Marketing Intern – AI/LLM Program - Your preferred name

Top Skills

Asana
Google Analytics
Hubspot
Semrush

Framework Security Marina del Rey, California, USA Office

4136 Del Rey Ave, Marina del Rey, CA, United States, 90292

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