Director, Generative AI Enablement

Hearst Technology Services is hiring a Director, Generative AI Enablement to help our organization achieve its technology vision.

In this role, you will develop and deliver AI "as-a-service" capabilities that empower our 360+ business brands on an opt-in basis.

As the Director, Generative AI Enablement, you will work in a fast-paced environment and be responsible for both guiding a team of technical specialists and performing hands-on work to build AI solutions that drive productivity, efficiencies, and revenue growth across our businesses.

You will have strong opinions and thought leadership on AI best practices and remain focused on serving the needs of our central IT department and operating companies.

Key Responsibilities:


* AI Service Development: Build and manage a portfolio of AI services and platforms (e.g.

generative AI models, automation tools) that business units can opt into.

Ensure these services are easily accessible, scalable, and secure, allowing our companies to leverage AI on demand for their specific and diverse needs.


* Cross-Functional Leadership: Lead agile teams (pods/squads of data scientists, engineers, and business analysts) to design, develop, and deploy AI solutions from concept to production.

Work collaboratively with business unit stakeholders in an iterative process to ensure solutions address real-world problems and are adopted successfully.


* Generative & Agentic AI Expertise: Provide technical direction in cutting-edge AI areas, including large language models (GPT), retrieval-augmented generation (RAG), and autonomous AI "agents." Guide the team in selecting the right approaches and tools for each project, and contribute hands-on to model development, validation, and integration when needed.


* Partner Integration: Collaborate with external service providers and vendors to augment our capabilities.

Evaluate and onboard third-party AI solutions or consulting partners where appropriate, managing these relationships to complement internal efforts and accelerate delivery of AI initiatives.


* Governance & Best Practices: Implement AI governance and best practices across projects.

This includes establishing guidelines for responsible and ethical AI usage (managing risks, bias, and accuracy), defining operational and support processes for AI solutions post-deployment, and ensuring compliance with data privacy and security standards.


* Operational & Engagement Models: Define clear engagement processes for business units to access AI services.

Develop chargeback or funding models for central AI offerings, ensuring transparency of costs.

Continuously refine how the central AI team works with divisions (e.g.

consulting, joint development, or self-service models) to maximize value and satisfaction.


* Performance Measurement: Monitor and report on the impact of AI solutions.

Track key success metrics such as efficiency gains, error reduction, revenue uplift, and user satisfaction.

Use th...