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Platform Product Manager, AI

Job in Richardson, Dallas County, Texas, 75080, USA
Listing for: RealPage, Inc.
Full Time position
Listed on 2026-01-01
Job specializations:
  • IT/Tech
    IT Project Manager, Product Designer
Job Description & How to Apply Below

Join to apply for the Platform Product Manager, AI role at Real Page, Inc.

Overview

The Platform Product Manager, AI will lead the execution and delivery of intelligent product capabilities using AI and associated technologies. This role requires strong technical product management skills, the ability to define and manage detailed product requirements, and a relentless focus on meeting delivery milestones and quality standards while enhancing resident lifecycle management, operational efficiency, and customer experience.

Responsibilities
  • Own sprint planning and backlog management, defining clear user stories, acceptance criteria, and technical requirements that enable the engineering team to build efficiently.
  • Drive execution of the product roadmap, managing milestones, dependencies, and timelines to ensure on‑time delivery of AI features within scope and quality targets.
  • Translate stakeholder needs into detailed product requirements (PRDs, technical specs, wireframes) and ensure builds meet functional and technical specifications.
  • Lead agile ceremonies (sprint planning, backlog refinement, retrospectives) and maintain prioritized backlogs that balance business value, technical feasibility, and resource capacity.
  • Partner closely with engineering teams throughout the development cycle to clarify requirements, validate builds, and resolve technical blockers.
  • Conduct acceptance testing and validation to ensure delivered features meet requirements, performance benchmarks, and quality standards before release.
  • Track and report on delivery progress, proactively identifying risks to timelines and implementing mitigation strategies to keep projects on schedule.
  • Manage scope and prioritize competing requirements from different business lines, making data‑driven decisions and adjusting direction when needed based on technical constraints or market feedback.
Qualifications
  • 5+ years of experience in product management with strong focus on execution and delivery, including 2+ years on AI/ML products.
  • Bachelor's degree in Computer Science, Engineering, or related field; advanced degree preferred.
  • Proven track record of shipping complex SaaS products on time using Agile methodologies.
  • Strong technical background with familiarity in AI/ML frameworks, data infrastructure, and software development processes.
  • Demonstrated success as a Product Owner managing scrum teams and delivering against aggressive timelines.
Knowledge, Skills, and Abilities
  • Exceptional organizational and project management skills with ability to manage multiple concurrent work streams.
  • Strong technical writing skills for creating detailed requirements documents, user stories, and technical specifications.
  • Proficiency with product management and agile tools (JIRA, Confluence, Aha, Miro, Figma).
  • Strong analytical and problem‑solving skills with data‑driven decision‑making approach.
  • Ability to assess technical feasibility and work effectively with engineering teams on implementation details.
  • Excellent written and verbal communication skills to articulate requirements, decisions, and trade‑offs to technical and non‑technical audiences.
  • Experience with user story mapping, wire framing, and defining product specifications.
  • Comfortable working in a fast‑paced environment with changing priorities and tight deadlines.
Key Performance Indicators (KPIs)
  • On‑Time Delivery: % of planned AI features and sprint commitments delivered on schedule and within scope.
  • Velocity & Throughput:
    Story points completed per sprint; features shipped per quarter against roadmap commitments.
  • Requirements Quality: % of user stories accepted without significant rework; clarity score from engineering team.
  • Release Quality:
    Post‑launch defect rates, bug severity, and production incidents for delivered features.
  • Sprint Predictability: % of sprint goals achieved; accuracy of sprint planning and estimation.
  • Milestone Achievement: % of roadmap milestones hit on target dates; average delay for missed milestones.
  • Stakeholder Satisfaction:
    Feedback scores from engineering, data science, and business teams on collaboration and requirements clarity.
  • Model Performance:
    Accuracy, precision, recall, or other relevant…
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