Staff Software Engineer

Job Description

ABOUT THE ROLE

Every roof, wall, and floor starts with a takeoff: measuring a project from plans, drawings, and imagery to determine exactly what materials it needs. Across our industry, that work is still largely done by hand. QXO is building the technology-forward leader in building products distribution, and takeoff is one of the first places we intend to change how the industry works.

As a Staff Software Engineer on our new Takeoff team, you will be one of the first engineers building the systems that measure a building and forecast what it takes to build it. You will design AI-powered products that turn an address, a set of plans, or an image into an accurate bill of materials, and take them from prototype to production across roofing, insulation, and exterior building products. The team is small by design, and the problems span computer vision, geometry, LLMs, and high-scale estimation.

You will build the way we build: AI-native. AI agents are a core part of how you design, write, test, and ship software, and you will set the standard for how the team does the same.

WHAT YOU WILL DO

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• Architect the measurement engine. Design and build the systems that extract measurements from aerial imagery, plans, drawings, and 3D models, and turn them into accurate, explainable quantities.
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• Forecast what it takes to build. Build the models that translate measurements into materials, including quantities, waste, and complementary products, and that improve as actual orders and job outcomes flow back in.
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• Put AI into production. Take LLM, machine learning, and computer vision capabilities from prototype to production with clear accuracy targets, evaluation harnesses, and human review where it matters.
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• Build for scale. Design services that handle high volumes of measurement and estimation requests with low latency, high reliability, and cost discipline, and expose them to web, mobile, internal tools, and partner platforms.
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• Expand across lines of business. Extend one takeoff platform from roofing to insulation, siding, waterproofing, decking, and beyond, so each new line of business ships faster than the last.
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• Engineer AI-native. Use AI agents across the software lifecycle, from design and code to testing and operations, and build the tooling, patterns, and review practices that make the team faster without lowering the bar.
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• Shape the direction. Partner with product, UX, and sales engineering leaders and with the takeoff experts who do this work today. Inform build, buy, and partner decisions with rigorous technical evaluation.
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• Raise the bar. Mentor engineers, lead design reviews, and set the standard for accuracy, quality, and operational excellence on the team.
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BASIC QUALIFICATIONS

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• 8+ years of experience designing, building, and operating production software systems, including technical leadership of complex, cross-team projects.
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• Hands-on experience building and shipping AI and machine learning systems in production, including practical experience with LLMs.
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• Experience building high-scale measurement, estimation, or forecasting systems, including defining accuracy metrics and improving them over time.
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• Strong foundation in distributed systems, data pipelines, and service design for high-volume, low-latency workloads.
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• An AI-native engineering practice: daily use of AI coding agents and tools, and experience building evaluations, guardrails, or tooling around AI systems.
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• Ability to turn ambiguous problems into clear technical designs and explain tradeoffs to engineering and business partners in plain language
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PREFERRED QUALIFICATIONS

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• Experience in construction technology, building products, estimating, or takeoff.
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• Background in computer vision, photogrammetry, or aerial and geospatial imagery.
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• Experience with computational geometry, CAD, or 3D modeling, and with delivering those experiences across web and mobile clients.
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• Experience with demand or quantity forecasting, probabilistic modeling, or time series methods.
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• Experience as an early engineer on a new product or team in a high-growth environment.
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• Advanced degree in computer science, machine learning, or a related field.
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