Principal Product Manager

Measurabl

2d•Remote

About The Position

We're hiring a Principal Product Manager to help define and build AI-powered capabilities across our sustainability data platform — shaping how AI shows up for the owners, operators, and investors who rely on our data every day. You'll bring two things together: deep product experience building for real estate organizations, and direct experience building with AI. You've shipped software that proptech companies, real estate data platforms, or real estate services firms rely on, and you understand how these organizations think, buy, and adopt technology. You've also either shipped an AI-powered product or feature yourself, and you use AI seriously in how you build product — research, specs, prototyping, synthesis — and can speak concretely to how it's changed your output. What You'll Help Define: Where AI belongs in the platform — identifying the highest-value places for AI to reduce manual work and surface insight across large real estate portfolios, and making the call on where it doesn't belong How we evaluate and trust it — working with data science and engineering to define what "good" looks like, how we catch degradation, and when a model's output needs a human in the loop The data foundation underneath it — ensuring the underlying data is structured and validated well enough to support AI-powered capabilities as they're built The roadmap itself — this role has real influence over what gets built and in what order, not just execution against a predefined plan What You'll Do: Shape the roadmap for AI-powered capabilities based on how real estate organizations actually work, translating real-world workflows into product requirements and measurable success criteria Own features end to end, including post-launch performance: accuracy over time, edge cases, and the tradeoffs between automation and human review Partner directly with customers managing billions in real estate assets to understand their needs and validate that AI-generated output meets their bar Work closely with data science and engineering to translate real estate domain requirements into specs, models, and evaluation frameworks they can build and test against Drive alignment across product, engineering, and go-to-market teams, often without direct authority Use AI tools in your own workflow to move faster and produce better product work

Requirements

8–10 years in product management with a track record of shipping successful B2B products, the majority of it building for real estate organizations — proptech, real estate data/technology platforms, or real estate services firms
Direct experience shipping at least one AI/ML-powered feature or product in production, or demonstrable, ongoing fluency using AI to do product management work itself
Comfortable enough with data and models to partner with data science and ML engineers on evaluation design, without needing to build the models yourself
Strong analytical and quantitative decision-making skills, with the judgment to know when a simpler, non-AI approach is the right call
A self-starter who thrives in ambiguity, moves fast with limited resources, and is comfortable making decisions with incomplete information
Genuine interest in sustainability and the belief that there's real product to build at the intersection of real estate and climate data
Analytical Rigor: Comfortable with financial models, data analysis, and quantitative decision-making
Startup Mentality: Self-starter who thrives in ambiguity and moves fast with limited resources
Bias for Action: Asks for forgiveness rather than permission; comfortable making decisions with incomplete information
Customer-Obsessed: Deep empathy for how real estate professionals analyze deals and make investment decisions
Mission-Driven: Passionate about sustainability and believes technology can drive meaningful impact in real estate
Builder's Mindset: Excited about creating products that solve complex real estate challenges

Nice To Haves

Real Estate Investment: Private equity, asset management, investment management, or fund management
Commercial Lending: Debt origination, underwriting, or loan servicing with focus on financial analysis
Real Estate Analysis: Appraisal, consulting, research, or analytics roles involving property evaluation
Capital Markets: REIT analysis, real estate securities, or institutional real estate investment

Responsibilities

Shape the roadmap for AI-powered capabilities based on how real estate organizations actually work, translating real-world workflows into product requirements and measurable success criteria
Own features end to end, including post-launch performance: accuracy over time, edge cases, and the tradeoffs between automation and human review
Partner directly with customers managing billions in real estate assets to understand their needs and validate that AI-generated output meets their bar
Work closely with data science and engineering to translate real estate domain requirements into specs, models, and evaluation frameworks they can build and test against
Drive alignment across product, engineering, and go-to-market teams, often without direct authority
Use AI tools in your own workflow to move faster and produce better product work