Responsibilities

• Own the Marketing AI roadmap: Setting and defending the use-case portfolio, including what gets built, in what order, and for whom, prioritized against reclaimed capacity and business impact
• Run the path from idea to production: Building and operating the intake stage-gate from idea to pilot to production to owned, including the handoff model that transfers run-state to the team accountable for the outcome
• Stand up the agent and orchestration platform: Owning the shared layer, reusable components, and the data and vendor integration that AI use cases depend on, focused on integration and orchestration rather than model building
• Own AI governance for Marketing: Running agent audits, brand-risk scoring, and exclusion zones in partnership with Legal and Brand, aligned to Zillow's AI Principles and to external standards
• Drive adoption across the org: Running the adoption program and the network of embedded AI liaisons so that capability is embedded in day-to-day workflows rather than sitting unused
• Build and lead the team: Hiring into net-new technical and strategic roles, integrating talent redeployed from across Marketing, and setting the performance bar for a newly formed team
• Report value to leadership: Owning the measurement of capacity gained, speed to market, and business impact, including a clear account of what did not work

Requirements

• 10+ years in marketing technology, growth engineering, applied AI, or technical product, including 4+ years leading teams.
• Production track record: Has moved AI use cases from proof of concept to scaled operation, and can speak specifically to what was built, what broke along the way, and what the measured impact was
• Marketing fluency: Strong understanding of how Marketing operate, with enough depth to hold a substantive conversation with a channel leader about where AI helps and where it does not
• Technically credible: Able to go deep with engineers on agent orchestration, data integration, and evaluation, and to distinguish a serious architecture from a demo, without needing to build models directly. Familiarity with a modern composable stack (CDP, reverse ETL, cloud data platform, enterprise LLM tooling) highly valued
• Enablement mindset: Track record running a center-led function that transferred capability outward as it matured, rather than accumulating ownership. Experience standing up a center of excellence or platform team from zero a plus
• Governance judgment: Experience managing brand, legal, and privacy risk in AI systems, and building the review mechanisms rather than resisting them
• Influence without authority: Able to drive outcomes that land inside other teams, on other roadmaps, without direct control
• Build-versus-buy judgment: Experience evaluating and managing AI and martech vendors, with a clear view of when a platform partner beats an internal build
• Bachelor's degree required; advanced degree in a technical or business field (MBA, Computer Science, Engineering, Analytics) a plus