We are seeking a hands‑on Product Director, AI/ML to lead strategy and execution for high‑impact AI/ML capabilities across the company. This role serves as the shared‑services AI/ML product lead, enabling commercial and internal product features with scalable, reusable, and compliant AI/ML capabilities. The roles begins as an Individual Contributor Director reporting directly to the VP, Product Management for the Lumina Data Platform, with the opportunity to grow into a people‑leadership role as our AI/ML requirements expand.
Additionally, this role has end‑to‑end product ownership for LLM capabilities within the Data & Analytics business unit—driving autonomous workflows, multi‑step reasoning agents, orchestrated task flows, and high‑value data‑intensive AI capabilities. This is a high‑visibility role ideal for a product leader who combines strong technical fluency, cross‑functional leadership, and drives execution across Product, Data Science and Engineering.
KEY RESPONSIBILITIES
1. AI/ML Product Strategy & Vision
Own the AI/ML capability roadmap and vision aligned to portfolio strategy.
Define multi‑quarter investment themes that balance internal acceleration with commercial product differentiation.
Identify opportunities where LLMs can accelerate classical ML cycles, including automated evaluation, data summarization, hypothesis generation, and model quality refinement.
2. Shared‑Services AI/ML Ownership
Serve as the central product lead for shared AI/ML components, including vector stores, RAG pipelines, evaluation harnesses, LLM safety tooling, feature stores, and model governance frameworks.
Drive adoption across multiple product lines, ensuring consistency, compliance, and time‑to‑value acceleration.
Reduce duplication and enable data science to build AI/ML capabilities faster and more safely.
3. LLM Ownership (Data & Analytics BU)
Own the full product strategy and delivery of LLM capabilities within the D&A business unit.
Define value propositions for autonomous AI agents, multi‑step reasoning systems, and orchestration frameworks tied to D&A customer outcomes.
Work closely with Product and AI Engineering leadership to take LLM features from concept to production with rigorous evaluation, reliability, and governance.
4. LLM‑Accelerated ML Development
Define and promote workflows where LLMs augment classical ML development, including:
Synthetic data generation
Automated documentation, explanations, and evaluation
Feature exploration and error analysis
Prompt engineering and safety reviews
5. Governance, Safety & Compliance
Embed safe‑by‑design principles into shared‑services and D&A AI/ML capabilities.
Partner with Governance, Legal, and InfoSec to ensure model transparency, auditability, and responsible‑AI compliance.
Establish best practices for prompt safety, hallucination mitigation, lineage, and monitoring of LLM capabilities.
6. Leadership & Future Team Development
Operate initially as an individual contributor Director with strong influence, cross‑functional leadership, and executive‑level communication.
As AI/ML investments scale, help define team structure and may assume direct people leadership responsibilities.
Mentor PMs and partner with Data Science and AI Engineering leaders to elevate AI product delivery maturity.
Required
9–12+ years in Product Management, Data Science, or ML‑adjacent fields for data-heavy B2B SaaS environments
3+ years hands‑on with LLMs/Generative AI (prompting, evaluations, RAG, agent systems).
Proven track record shipping ML‑powered products with measurable business outcomes.
Strong understanding of ML lifecycle, experimentation, and MLOps.
Ability to translate complex AI concepts to technical and non‑technical stakeholders.
Deep collaboration experience with Data Science and Engineering teams.
Preferred
Experience with Azure ML, AWS SageMaker, or GCP Vertex AI.
Familiarity with OpenAI, Claude, Gemini, LangChain, LangSmith, agent frameworks, vector databases, and embedding models.
Experience with data governance, lineage, and compliance.
Background in multifamily real estate or proptech.
SUCCESS METRICS
Adoption of shared AI/ML capabilities across multiple product groups.
Reduction of redundant ML efforts and faster experimentation cycles.
Delivery of LLM product capabilities in D&A that drive quantifiable customer and business outcomes.
Reliability, safety, and governance adherence across all deployed AI/ML systems.
Improved ML development velocity through LLM‑assisted workflows.
HOW YOU’LL WORK
Report directly to the VP, Product Management for the Lumina Data Platform, partnering closely on platform‑aligned AI/ML strategy.
Serve as both: (1) the shared‑services AI/ML product lead enabling multiple BUs; and (2) the dedicated LLM product lead for the D&A BU.
Drive alignment, clarity, outcomes, and execution across DS, Engineering, Governance, Platform, and Product organizations.
Foster a high‑trust culture centered on learning, experimentation, and rapid value delivery.
SALARY AND BENEFITS
Compensation may vary depending on your location, qualifications including job-related education, training, experience, licensure, and certification, that could result at a level outside of these ranges. Certain roles are eligible for additional rewards, including annual bonus, and sales incentives depending on the terms of the applicable plan and role as well as individual performance.
Equal Opportunity Employer: RealPage Company is an equal opportunity employer and committed to creating an inclusive environment for all employees.
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