Overview
 

We are seeking a Content Strategist who understands how agentic commerce transforms content from static marketing assets into structured, machine-interpretable systems that power discovery, decisioning, and autonomous transactions.
 

This role blends content strategy, information architecture, semantic modeling, and applied AI literacy with a deep understanding of Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO). You will architect AI-native, agent-compatible content ecosystems that are brand-forward, structurally precise, and continuously
 
optimized
 
through signals, metadata, and feedback loops.
 

These content systems will enable brands to perform effectively in environments where intelligent agents shape discovery, interpret structured information, and increasingly act on behalf of customers.
 

 

Job Responsibilities
 

Content Architecture for AI-Native Commerce Ecosystems
.

 
Designing structured content systems that enable intelligent agent reasoning and optimization, including:
 

Developing modular content architectures that support reuse, recombination, and personalization across channels.
 

Defining taxonomies, ontologies, and metadata schemas that dramatically improve agent comprehension and retrieval accuracy.
 

Designing content models that enable structured comparison, decision support, and generative reinterpretation.
 

Ensuring product, service, and policy content is machine-readable, semantically rich, and aligned
 
to
 
agent-driven discovery patterns.
 

 

GEO & AEO Content Strategy
.

 
Building content systems
 
optimized
 
for LLM-mediated search, answer engines, and agent-driven journeys, including:
 

Identifying
 
priority content domains that influence agent recommendations and autonomous decision-making.
 

Designing structured content frameworks that enhance findability, answer precision, and authoritative positioning.
 

Partnering with GEO practitioners to translate model insights into content refinements and structured improvements.
 

Establishing standards for multimodal content (text, visual, structured data) that support generative outputs and adaptive responses.
 

 

Modular Creative & Narrative Systems
.

 
Ensuring brand storytelling translates effectively into machine-operable structures, including:
 

Designing modular messaging systems that preserve brand integrity while enabling dynamic recombination.
 

Identifying
 
controllable content variables—tone, framing, attributes—that can be tuned and optimized over time.
 

Translating brand voice into structured components that conversational and AI systems can deploy consistently.
 

Collaborating with Creative, Conversation Design, and Experience teams to ensure content systems support cohesive agent-mediated journeys.
 

 

Optimization-Centered Content Governance
.

 
Embedding experimentation and continuous improvement into the content lifecycle, including:
 

Designing
 
experiments that test narrative structures, attribute framing, metadata schemas, and structured content variations.
 

Establishing performance measurement frameworks tied to agent retrieval, recommendation frequency, and conversion influence.
 

Translating optimization outcomes into scalable governance standards for marketing, commerce, and CX teams.
 

Ensuring content ecosystems evolve continuously through systematic testing, signal analysis, and model feedback loops.
 

 

Enterprise Content Enablement & Cross-Functional Leadership
.

 
Operating at a level to drive alignment across large organizations, including:
 

Leading cross-functional workshops to align marketing, commerce, product, legal, and technology teams around AI-native content strategy.
 

Defining enterprise-wide content standards that enable scalability and long-term governance.
 

Advising clients on content operating model transformation required for agentic commerce.
 

Providing
 
strategic guidance to senior stakeholders on risks, opportunities, and competitive positioning in AI-mediated ecosystems.