Lead Product Manager, AI Strategy

About the role

Realtor.com® is the No. 1 site trusted by real‑estate professionals, connecting buyers, sellers, and renters with insights and guidance to find their perfect home. The company is seeking a Lead Product Manager to define the vision and strategy for AI‑native product experiences that transform how clients interact with Realtor.com’s products, integrate data and insights into client workflows, and deliver scalable backend integrations for enterprise brokerage ecosystems.

Responsibilities

• Define the vision for how clients interact with RDC’s products in an AI‑native model, reimagining traditional workflows around conversational, proactive, and insight‑driven experiences rather than bolting AI onto existing screens.
• Own the product strategy and roadmap for an AI‑native interaction model across the client portfolio, spanning client‑facing products, internal tools, and data products that package RDC’s data and insights for external use.
• Translate broader Core Product Strategy priorities into concrete, sequenced AI product bets, in partnership with the Advanced Insights sub‑team and other client product areas.
• Define the north star for AI‑native capabilities and partner with data science and engineering to ensure underlying data and technical strategies support that need, covering model selection, data quality, pipeline and infrastructure requirements, and scaling from prototype to production.
• Define the data requirements that underpin new AI capabilities, including what data needs to be captured, cleaned, or integrated, and work with data teams to close gaps.
• Set and defend quality, accuracy, and trust standards for client‑facing AI outputs, understanding where model limitations create real risk to clients and the business.
• Build the business case for new AI capabilities, including expected client and business impact, technical cost and complexity, and buy‑vs‑build‑vs‑partner tradeoffs.
• Design internal AI tools that make client‑product, sales, and support teams more effective at serving clients, from insight generation to workflow automation.
• Define and grow RDC’s data product strategy, identifying which data and insights can be packaged and sold to clients and partners, and what it takes technically and commercially to deliver them responsibly and at scale.
• Design scalable backend integrations that give large enterprise segments direct access to RDC’s data and insights, integrated into their own brokerage ecosystems.
• Partner with enterprise and partnership stakeholders to shape the data‑access and integration strategy for the largest accounts, balancing client value against data‑governance and commercial considerations.
• Stay ahead of the external AI landscape, competitor capabilities, and emerging techniques, and translate what matters into RDC’s product strategy.
• Partner directly with executive stakeholders—including GMs and the Strategy team—to define where AI creates real value for RDC and align that view with the broader portfolio strategy.
• Collaborate with legal, privacy, and trust‑and‑safety functions to navigate data and model risks specific to AI products.
• Represent AI product strategy in planning and review forums, communicating tradeoffs and progress clearly to both technical and non‑technical audiences.

Requirements

• Deep hands‑on experience building and shipping AI‑native, client‑facing products, not just experimenting with AI internally.
• Track record of designing new interaction models—conversational, proactive, or insight‑driven—rather than merely adding AI features to existing workflows.
• Working technical fluency in AI product construction: model types and tradeoffs, data pipelines, evaluation and monitoring, and infrastructure choices affecting cost and scale.
• Comfort partnering closely with engineering and data science as a peer in technical conversations, not just a translator of requirements.
• Understanding of operational and technical requirements needed to serve AI capabilities reliably to real clients at scale.
• Strong product judgment on where AI creates genuine client value versus novelty, with the discipline to say no to the latter.
• Experience defining or scaling data products, including packaging data and insights into externally sellable offerings (strong plus).
• Comfort working with enterprise or B2B stakeholders on data access, integration, and partnership strategy for large accounts.
• Experience defining and enforcing quality and trust standards for AI outputs in client‑facing products.
• Strong cross‑functional collaboration skills to align data science, engineering, design, legal, and business stakeholders around a single roadmap.
• Clear written and verbal communication, able to explain technical AI tradeoffs to non‑technical stakeholders and vice versa.
• Bachelor’s degree in a technical field or equivalent experience; background in data science, engineering, or applied AI is a strong plus.
• 10+ years of product management experience, including recent experience shipping AI or ML‑powered features in a client‑facing product.
• Demonstrated experience partnering directly with data science and engineering teams on model selection, evaluation, and scaling decisions.
• Experience building both client‑facing and internal‑facing tools (plus).
• Experience with enterprise or B2B data integrations, APIs,