AI Product Management Director

RealPage•Richardson, TX

About The Position

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.

Requirements

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.

Nice To Haves

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 .

Responsibilities

Lead shared ‑ services AI/ML product capabilities used across multiple product lines.
Partner with platform, data science, engineering, and BU product leadership to align on AI/ML vision , drive roadmap, execution and capacity management .
Oversee roadmap and delivery for Agentic AI within the Data & Analytics business unit.
Influence long ‑ term organizational design and may take on people leadership as the function scales.
Balance commercial and internal product priorities, maintaining an investment strategy aligned to enterprise and BU strategic goals
Own product strategy and delivery for AI governance and ML Ops, establishing robust frameworks for model lifecycle management, compliance, and operational excellence.
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.
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.
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.
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
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 .
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.