Engineering Manager, Estimation

Why Hover wants you The Estimates Platform team owns the foundational systems that determine what Hover can scope, measure, and estimate for any structure. If a product needs to know what work a structure requires or what it costs, it starts here. As Engineering Manager, you’ll lead the team building the classification and scoping systems that power Hover’s estimates pipeline—integrating tightly with 3D model data, external partners, and downstream products. You’ll translate rich property data into structured, actionable estimates and ensure these systems are accurate, reliable, and ready to scale. You will contribute by Own the technical roadmap and business strategy for the Estimates Platform, balancing quarterly delivery with long-term architectural vision. Synthesize inputs from Product, Data Science, Operations, and business stakeholders into a clear technical strategy that delivers incremental value. Lead, mentor, and grow a team of engineers—supporting career development, promotions, and a high-performance culture. Partner cross-functionally with Product, Operations, 3D Modeling, and external integration partners to translate requirements into actionable plans. Drive the reliability, accuracy, and scalability of the classification and scoping systems that power estimates across Hover’s product surface. Balance innovation with operational stability, continuously improving system health and data quality. Your background includes 5+ years as a hands‑on engineer, with experience designing and delivering production systems at scale. 2+ years leading engineering teams, with a track record of guiding technical teams and collaborating across stakeholders to drive business-wide impact. Experience operating in a fast‑paced, product‑driven technology environment. Experience building or 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. 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). Exposure to machine learning–assisted classification or data enrichment pipelines. Experience working with 3D model data, geospatial systems, or computer vision outputs as inputs to downstream business logic. Background in building or scaling rules engines, configuration‑driven systems, or decision frameworks that non‑engineers can extend. Comfort operating in a domain with complex, evolving data—where "correct" is a moving target and iteration speed matters as much as precision. Compensation - Competitive salary and meaningful equity in a fast‑growing company. Healthcare - Comprehensive medical, dental, and vision coverage for you and dependents. Paid Time Off - Unlimited and flexible vacation policy. Paid Family Leave - We support work/life balance and offer generous paid parental and new child bonding leave. Mandatory Self‑Care Days - A day set aside each month to allow employees to recharge. Remote Wellbeing Resources - We provide recurring fitness classes, meditation/mindfulness tools, virtual therapy, and family planning assistance. Learning - We encourage continued education and will help cover the cost of management training, conferences, workshops, or certifications. Hybrid roles at Hover Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50‑mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles. The US base salary range for this full‑time position is $190,000 – $235,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job‑related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. #J-18808-Ljbffr Hover