Lead, Enterprise AI Content Platform

Hearst

New York (NY)

Hybrid

USD 175,000 - 195,000

Full time

14 days+

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Benefits offered by this job

Medical

Dental

Vision

Disability insurance

Life insurance

401(k)

Paid holidays

Paid time off

Employee assistance programs

Job summary

Hearst seeks a Senior Product Manager for the AI Content Platform to lead strategy, development, and evolution of the enterprise AI content platform powering AI-driven search, personalization, and recommendations across Hearst. You’ll own the vision and execution for semantic enrichment, embeddings, knowledge graphs, and metadata to transform content into structured, machine-understandable assets.

The ideal candidate combines deep product management experience with a strong understanding of AI,

Qualifications

7–10 years of product management experience in enterprise platforms or AI-powered products.
Strong understanding of modern AI technologies including LLMs, RAG, vector embeddings, semantic search and knowledge graphs.
Experience with vector databases, search technologies, metadata management, and content processing pipelines.
Experience defining product strategy, roadmaps, requirements, and success metrics for highly technical platforms.
Strong analytical and systems-thinking skills with ability to translate emerging technologies into scalable enterprise capabilities.
Excellent communication skills with experience influencing senior leadership and aligning cross-functional stakeholders around long-term platform strategy.
Bachelor's degree required; advanced degree in Computer Science, Data Science, Engineering, Information Science, or related field preferred.

Responsibilities

Own the product strategy, roadmap, and execution for Hearst's enterprise AI Content Platform, serving as the foundation for AI-powered products and services across the company.
Lead development of enterprise content intelligence capabilities including vector embeddings, semantic search, knowledge graphs, ontology management, metadata enrichment, entity extraction, and AI-driven content understanding.
Define the product vision for scalable content processing pipelines that transform editorial content into AI-ready assets supporting retrieval, recommendation, personalization, and generative AI applications.
Partner closely with Engineering, Product, and business stakeholders to prioritize platform capabilities and deliver enterprise solutions.
Drive development of semantic search, vector databases, retrieval pipelines, and RAG capabilities that improve discoverability and AI performance.
Evaluate emerging AI technologies, foundation models, embedding models, vector databases, and semantic technologies to continuously improve platform capabilities.
Translate complex AI and machine learning concepts into product requirements and actionable engineering roadmaps.
Serve as the product leader for enterprise content intelligence, enabling downstream personalization, advertising, audience insights, and AI-powered consumer experiences.