Staff Content Architect

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

This role is based in either New York, Sunnyvale, San Francisco, Mountain View, or Chicago

The Knowledge Management Solutions (KMS) team at LinkedIn is responsible for creating and delivering self-service content for LinkedIn’s members, customers, and employees. The team creates instructional, procedural, and technical content using both traditional and AI-powered methods. This content is made available externally through LinkedIn's help centers, virtual chat assistants, and in-product experiences (including those powered by AI/GAI), and internally through enterprise search systems and CRMs.

We are seeking a Staff Content Architect to own the design, governance, and evolution of our structured content and data model ecosystem. This role is foundational to ensuring the long-term scalability, integrity, and ROI of LinkedIn’s content systems as we transition to AEM Guides and expand AI-driven self-service experiences.

This is a highly strategic role responsible for defining the “what and why” of our content architecture—ensuring that content structures, metadata, and reuse patterns scale effectively across products, platforms, and AI use cases. This role works in close partnership with Content Strategy leaders, Taxonomy, and Knowledge Engineering to translate user needs and business requirements into scalable, well-governed content architecture. The role focuses on content architecture while partnering closely with platform engineering teams responsible for implementation and system configuration.

Key Responsibilities

• Serve as the single accountable owner for the KMS DITA content model, driving design, governance, and ongoing evolution to ensure scalability, reuse, and long-term system integrity
• Define and enforce structural standards, metadata models, taxonomy alignment, and reuse strategies; partner closely with the Taxonomist to ensure consistent and scalable classification and controlled vocabularies
• Partner with Content Strategy leads and teams to align content architecture with user needs, editorial intent, and business goals—translating content strategy into scalable structural design
• Translate content and data model into operational implementations (templates, authoring patterns, validation rules, workflows), ensuring consistent adoption across authors, teams, and partners
• Establish and enforce governance frameworks, review mechanisms, and escalation paths to prevent structural drift, duplication, and deviation from defined standards across internal and external contributors
• Design content structures optimized for AI, search, and automation; partner with Engineering, Search, and AI teams to improve discoverability, retrieval accuracy, and overall content performance
• Define durable integration patterns across AEM Guides, Help Center, CRM systems, content data platforms, and AI pipelines to ensure seamless interoperability across the ecosystem
• Lead architectural alignment across transformation initiatives (AEM Guides, Help Center redesign, AI-driven support), including defining strategies for migration, normalization, and legacy content rationalization
• Partner with Product, Content Strategy, and Engineering to ensure content architecture decisions enable intuitive, efficient authoring experiences and reduce reliance on manual workarounds
• Drive measurable impact by improving content reuse, reducing translation costs, and scaling operations; define and track architecture health metrics (e.g., reuse efficiency, metadata consistency, search effectiveness, authoring efficiency)
• Reduce long-term risk and reliance on external consultants by establishing durable internal frameworks, standards, and governance models for content architecture

Basic Qualifications

• Bachelor’s degree in Computer Science, Information Architecture, Content Engineering or related field
• 8+ years of experience in content architecture, knowledge management, content systems, or structured authoring
• 8+ years in DITA (structured content methodology) and topic-based authoring
• 5+ years of experience working with enterprise content management systems such as AEM Guides
• 5+ years of experience designing metadata models, taxonomy, and content reuse strategies
• 5+ years of demonstrated ability to lead and influence cross-functional stakeholders without direct authority

Preferred Qualifications

• Experience building or governing content models for AI/ML-powered systems or conversational interfaces
• Strong understanding of the content lifecycle across authoring, publishing, localization, and consumption
• Experience designing integrations across content ecosystems, data platforms, and downstream systems
• Experience collaborating with taxonomy and metadata specialists to design scalable classification and retrieval systems
• Familiarity with search optimization, semantic tagging, and knowledge graph concepts
• Experience driving cross-team adoption of structured content models across distributed authoring teams and external partners
• Strong analytical and systems thinking mindset
• Excellent stakeholder management and executive communication skills

Suggested Skills

• Structured content architecture and DITA content modeling
• AI-ready content design, search optimization, and content discoverability
• Metadata strategy, taxonomy alignment, and content reuse governance
• Cross-functional influence, stakeholder alignment, and executive communication

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $115,000 to $186,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits, and/or other applicable incentive compensation plans. For more information, visit .

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