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Director of Content Engineering
Company: College Board
Employment Type: Full-Time
Location: 100% Remote – USA (occasional travel for business meetings)
Compensation: $80,000 – $140,000 (USD, location-adjusted)
Category: Software Engineering & Development
Close date or Apply by date: Open until filled
WHY THIS ROLE MADE THE CUT
Fully remote (no hybrid or office requirements)
Full-Time role
Job is listed on company site with a direct link to apply
Legitimate, established company
Posted within the last 14 days OR includes a clear deadline to apply
Clear salary range is disclosed
ROLE SNAPSHOT
College Board is hiring a Director of Content Engineering to lead a team of six content engineers working across Drupal, DITA/XDocs, headless/decoupled content APIs, and item-authoring systems while serving as hands-on expert in DITA and modular structured authoring. You'll guide and grow a multidisciplinary team developing content structures and processes, work directly within DITA/XDocs environment to improve topic structures and reuse patterns, expand usage of the system to include new content and publish for wider platforms, partner with design systems and frontend engineering to ensure structured content aligns with component-driven UI, and collaborate with engineering teams on transformations and APIs connecting authoring systems. This player/coach leadership role requires deep hands-on expertise with DITA and DITA-based authoring systems, experience designing and maintaining structured content models, proven ability to lead and mentor content engineering teams, and strong collaboration across design, engineering, and content disciplines.
KEY WORDS TO INCLUDE IN YOUR RESUME/COVER LETTER IF YOU APPLY:
DITA and structured content authoring
Content engineering leadership
Drupal and decoupled CMS
Content modeling and metadata design
Team leadership and mentorship
Content APIs and integrations
XDocs or similar authoring systems
Cross-functional collaboration
Content workflow optimization
Taxonomy and content governance
Keywords are suggested based on the language used in the employer's job description to help applicants align with automated screening systems.
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