Senior Technical Program Manager, Fub Engineering

Zillow Zillow · Consumer · United States · Remote

Senior Technical Program Manager (P4) on the Follow Up Boss (FUB) & Partner team at Zillow. Leads cross-functional technical and product programs spanning multiple teams and quarters, focusing on large, ambiguous initiatives including platform infrastructure, AI capabilities, partner integrations, and customer experiences. Partners with Engineering and Data Science to deliver AI/ML-enabled capabilities end-to-end, including model integration, experimentation, evaluation, rollout strategies, and post-launch monitoring, while ensuring responsible AI practices and quality measurement.

What you'd actually do

  1. Own complex, multi-team programs across Engineering, Product, Data Science, Design, Marketing, Partnerships, and external partners, driving execution for high-impact initiatives in the FUB ecosystem.
  2. Drive alignment across organizational boundaries by surfacing dependencies and misalignments early, engaging leadership with clear trade-offs, risks, and decision frameworks.
  3. Lead both engineering-focused initiatives (such as platform modernization, reliability improvements, API evolution, and data and AI infrastructure) and customer-facing product programs (such as new FUB capabilities, partner workflow enhancements, monetization initiatives, and cross-platform launches).
  4. Partner with Engineering and Data Science to deliver AI- and ML-enabled capabilities end to end, including model integration, experimentation, evaluation, rollout strategies, and post-launch monitoring, while ensuring responsible AI practices and quality measurement.
  5. Define success metrics, track program health across delivery, quality, and business impact, and establish scalable mechanisms that improve engineering velocity and cross-team execution.

Skills

Required

  • 5+ years of experience in technical program management or software program management in complex, cross-functional environments.
  • Experience leading both infrastructure/technical programs and customer-facing product initiatives.
  • Experience working with modern web and mobile architectures, distributed systems, and APIs in agile environments.
  • Knowledge of the AI/ML product development lifecycle, including experimentation, deployment, evaluation, and monitoring.
  • Ability to identify dependencies across systems, teams, and partners, bring clarity to ambiguous environments, and think in systems about how technical investments enable product velocity and long-term scalability.
  • Excellent written and verbal communication skills, with the ability to engage both technical and non-technical stakeholders and influence without formal authority.
  • Strong analytical and problem-solving skills, including assessing trade-offs and making data-informed decisions.

What the JD emphasized

  • AI capabilities
  • AI/ML product development lifecycle
  • model integration
  • experimentation
  • evaluation
  • rollout strategies
  • post-launch monitoring
  • responsible AI practices
  • quality measurement