Engineer - Commercial Roofing

About the company Asseti is the category-defining platform for asset intelligence and operations, used by some of the world's largest real estate owners to understand their assets, optimise portfolio performance, and make smarter operational, maintenance, and capital decisions. We turn complex, fragmented asset information into a single source of truth, combining real-time condition insights with the operational context needed to prioritise work, manage risk, and drive efficient action across large property networks. Asseti automates condition detection, triage, repair prioritisation, and cost forecasting at scale. We're building the intelligence and operational backbone that helps leading organisations run their assets with clarity, consistency, and confidence. The opportunity As we scale across some of the largest commercial property portfolios in the US, we're embedding domain expertise directly into our platform. We work with leading field professionals to ensure our AI-driven assessments reflect real-world inspection standards and decision making. This engagement is about quality and rigour, making sure what our platform sees and scores matches what an experienced inspector would find on the ground. This is an independent contractor role. Hours will vary based on project needs. The role You'll review drone and aerial imagery of large commercial roofs and help us define and validate our condition and defect identification methodology. Working directly with our product team, you'll tell us what to look for, how to classify it, and what makes something urgent. Your expertise will be translated into the assessment framework that drives our platform at scale. No site visits required. This is a fully remote engagement. What you will do Identifying and classifying defects visible from drone and aerial imagery Defining severity levels for each defect type Telling us what should trigger an urgent repair vs a monitor vs a replacement recommendation Helping us understand what we might be missing in our current approach