opengreenhousegv
Engineering Manager, Estimation
HOVER
Locationsan_francisco, San Francisco / New York
Last observed2026-06-13 05:23:26.446512
Job idgv-hover:greenhouse:7749400
Hover helps people design, improve, and protect the properties they love. With proprietary AI built on over a decade of real property data, Hover answers age-old questions like “What will it look like?” and “What will it cost?” Homeowners, contractors, and insurance professionals rely on Hover to get fully measured, accurate, and interactive 3D models of any property — all from a smartphone scan in minutes. At Hover, we’re driven by curiosity, purpose, and a shared commitment to serving our customers, communities, and each other. We believe the best ideas come from diverse perspectives and are proud to cultivate an inclusive, high-performance culture that inspires growth, accountability, and excellence. Backed by leading investors like Google Ventures and Menlo Ventures, and trusted by industry leaders including Travelers, State Farm, and Nationwide — we’re redefining how people understand and interact with their spaces. Why Hover wants you The Estimates Platform team owns the foundational systems that determine what Hover can scope, classify, and price for any structure. If a product needs to know what work a structure requires or what it costs, it starts here. At its core, this is a recommendation system. You'll ingest disparate data sources (3D model outputs, product catalogs from distribution partners, pricing feeds, and customer inputs), synthesize them into a structured language the rest of Hover can consume, and serve actionable estimates to internal teams, contractors, and insurance partners. The system is deterministic today, and the core stays that way. AI is how we accelerate the platform's expansion: ingesting new partner catalogs, classifying unfamiliar trades, and learning from every estimate that flows through. As Engineering Manager, you'll lead that evolution, extending the rules-based foundation with AI-driven capabilities that open the platform to new trades and new partners. You will contribute by Own the technical roadmap and business strategy for the Estimates Platform, balancing quarterly delivery with long-term architectural vision. Lead, mentor, and grow a team of engineers, supporting career development, promotions, and a high-performance culture. Drive AI adoption inside the team, pushing engineers toward AI-first workflows and tooling. Partner with Product to extend the platform with AI-driven capabilities that accelerate expansion into new trades, distributors, and partner catalogs. Navigate tradeoffs when Insurance and Construction need different things from the same platform, and communicate the why to each stakeholder. Work across Product, Data Science, Operations, 3D Modeling, and external integration partners to turn ambiguous business problems into scoped engineering work. Drive the reliability, accuracy, and scalability of the classification and scoping systems that power estimates across Hover's product surface. Your background includes 7+ years as a hands-on engineer, with experience designing and delivering production systems at scale. 3+ years leading engineering teams, with a track record of growing engineers, navigating stakeholder priorities, and driving business-wide impact. Experience building and owning platform-layer systems (classification engines, data pipelines, rules engines, or similar foundational infrastructure). Strong product intuition and comfort translating ambiguous business problems into clear, scoped engineering work. Active, daily user of AI coding tools, with experience coaching engineers on your team toward AI-first workflows. Experience shipping AI-driven capabilities into customer-facing products. Nice to haves: Experience in proptech, insurtech, construction tech, or domains involving structured property data or physical-world classification. Familiarity with building systems that integrate with external data providers or third-party estimation APIs (e.g., Xactimate, CoreLogic, or similar). Experience shipping production ML, inference, or recommendation systems
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