Senior Program Manager, GTM & Field Enablement at Greenhouse

Greenhouse

RemoteSeniorProduct Marketing, Productai

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Skills in this role

AI fundamentals
LLM evaluation

Courses relevant to this posting

Relevance is based on skills and concepts — not a guarantee that you qualify.

Designing Information Systems for AI Agent Consumption
Covered skills:AI fundamentalsLLM evaluation
Skills to close:None listed

Build the skills for this job

Coming-soon courses matched to this posting — outline, waitlist, and skill path.

Course DNA for this role

Designing Information Systems for AI Agent Consumption

7 chapters · 32 lessons

1. How Agents Read and Extract Information
4 lessons
Understand the technical pipeline agents use to fetch, parse, and extract meaning from web pages and documents.
2. Structured Data and Semantic Markup Fundamentals
5 lessons
Apply schema vocabularies, JSON-LD, and metadata patterns to make facts explicit and extractable.
3. Content Architecture for Agent Legibility
5 lessons
Design page structures, navigation, and content hierarchies that support both human and machine comprehension.
4. Retrieval-Augmented Generation in Practice
4 lessons
Understand how RAG systems combine search, embeddings, and language models to ground agent responses.
5. API and Data Interface Design for Agents
5 lessons
Build machine-first interfaces that expose product, inventory, policy, and transactional data in agent-friendly formats.
6. Auditing and Optimizing for Agent Readability
4 lessons
Evaluate existing content and systems, identify friction points, and prioritize improvements for agent workflows.
7. Real-World Applications Across Domains
5 lessons
Apply agent-first design principles to commerce, documentation, policy systems, and enterprise knowledge bases.

Want the full course when it launches? Join the waitlist and we will notify you.

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Skills in this role

Courses relevant to this posting

Build the skills for this job

Designing Information Systems for AI Agent Consumption

1. How Agents Read and Extract Information

2. Structured Data and Semantic Markup Fundamentals

3. Content Architecture for Agent Legibility

4. Retrieval-Augmented Generation in Practice

5. API and Data Interface Design for Agents

6. Auditing and Optimizing for Agent Readability

7. Real-World Applications Across Domains

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