Senior Product Manager, AI, NYT Wirecutter

Mission Overview & Responsibilities: 

Wirecutter, the product recommendation service from The New York Times, is looking for an experienced and driven Senior Product Manager, AI to lead the strategy and rapid experimentation of our AI initiatives.

You will be a catalyst for innovation, navigating the evolving landscape of LLMs and agentic flows. You will go from 0 to 1, building hands-on prototypes and proofs of concept to identify opportunities that amplify our value to readers and operational efficiency.

This is a remote position. You will report to the Product Director, Growth, NYT Wirecutter.

Responsibilities:

AI Strategy & Business Impact

• Strategic Planning: Create product plans focused on integrating AI to amplify reader services, improve operational efficiency, and optimize commerce initiatives. This includes developing strategies that balance immediate impact with long-term innovation.

• Prioritization: Guide the prioritization of AI work by building business cases that consider the bottom line and impact on key metrics. Knowing when to go deep on a specific use case versus broad experimentation will be key.

• Subject Matter Expertise: Serve as a subject matter expert on new technologies (LLMs, generative AI) and industry trends, translating them into actionable opportunities for the business.

• Market Intelligence & Foresight: Act as the primary advisor to Wirecutter leadership on the bleeding edge of the AI landscape (e.g., AEO/GEO, agentic flows, frontier model advancements, applications of AI in the industry). Provide synthesized insights and strong opinions on how shifts in consumer behavior, traffic, and technology should influence our long-term strategy.

AI Tooling, Development & Platform Innovation

• Rapid Prototyping & Validation: Drive a "test and learn" culture by creating rapid, low-fidelity to high-fidelity prototypes. You will validate hypotheses regarding reader-facing features and assist in translating validated ones to feature teams for productizing.

• Scope Management: Break large AI projects down into smaller, actionable scopes to mitigate delivery risk and provide near-term and long-term value.

• Metrics & Optimization: Develop metrics to monitor the impact of AI solutions on editorial quality, efficiency, reader engagement, and commercial performance, using data to drive iteration.

• Internal Tooling Enablement: Identify high-friction internal workflows and demonstrate how AI tools can automate inefficiencies. You won't just recommend tools; you will help teams implement and integrate them to demonstrate immediate efficiency gains.

AI Evangelism & Adoption

• Collaborative Influence: Work across reader-facing product development teams to identify their pain points and how they can use AI to help solve their problems. Build trust by demonstrating how AI can accelerate existing goals.

• Operational Evangelism: Champion the adoption of modern AI-assisted workflows across the organization. Organize demos, share "wins," and upskill product and engineering peers on utilizing AI accelerators (like coding assistants or automated QA) to improve velocity and developer happiness.

• Ethical Stewardship: Champion the ethical and responsible use of AI, ensuring tools uphold accuracy, objectivity, and reader trust.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications: 

• 5+ years of experience in product management.

• 2+ years of experience in AI/ML product management or applying AI tools to enhance workflows and execution.

• Experience partnering with engineers and data scientists to deliver complex technical solutions.

• Experience building your own prototypes, scripts, or lightweight proofs-of-concept.

• Understanding of how and when to use AI/ML-based solutions to solve business and customer problems.

• Experience discussing technical dependencies and system architecture with engineering and data science teams.

Preferred Qualifications: 

• Comfortable operating in a 0 to 1 environment where resources are constrained, and you rely on creativity and prototyping tools to prove value.

REQ-019334

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