Senior Software Engineer
QXO
Job Description
ABOUT THE ROLE
\n \nEvery 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.
\nAs a Senior 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 build 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.
\nYou 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 help shape how the team does the same.
\n \nWHAT YOU WILL DO
\n- \n
- Build the measurement engine. Design, build, and own core components of the systems that extract measurements from aerial imagery, plans, drawings, and 3D models, and turn them into accurate, explainable quantities. \n
- Forecast what it takes to build. Build and tune 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. \n
- Put AI into production. Ship LLM, machine learning, and computer vision features to production with clear accuracy targets, evaluation harnesses, and human review where it matters. \n
- Build for scale. Build 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. \n
- Expand across lines of business. Deliver takeoff features for roofing, insulation, siding, waterproofing, decking, and beyond, building reusable components so each new line of business ships faster than the last. \n
- Engineer AI-native. Use AI agents across the software lifecycle, from design and code to testing and operations, and contribute the tooling and patterns that make the team faster without lowering the bar. \n
- Work close to the customer. Partner with product, UX, and sales engineering and with the takeoff experts who do this work today to understand the workflow and turn it into working software. \n
- Own what you ship. Write design docs, review code, mentor engineers, and own the accuracy, quality, and operations of your systems in production. \n
BASIC QUALIFICATIONS
\n- \n
- 5+ years of experience designing, building, and operating production software systems, including leading the design and delivery of significant features or services. \n
- Hands-on experience building and shipping AI or machine learning features in production, including practical experience with LLMs. \n
- Experience building measurement, estimation, or forecasting systems at scale, including tracking accuracy and improving it over time. \n
- Solid foundation in distributed systems, data pipelines, and service design for high-volume, low-latency workloads. \n
- An AI-native engineering practice: daily use of AI coding agents and tools, and experience applying evaluations or guardrails to AI features. \n
- Ability to take a loosely defined problem to a working design and explain tradeoffs to engineering and business partners in plain language \n
PREFERRED QUALIFICATIONS
\n- \n
- Experience in construction technology, building products, estimating, or takeoff. \n
- Background in computer vision, photogrammetry, or aerial and geospatial imagery. \n
- Experience with computational geometry, CAD, or 3D modeling, and with delivering those experiences across web and mobile clients. \n
- Experience with demand or quantity forecasting, probabilistic modeling, or time series methods. \n
- Experience as an early engineer on a new product or team in a high-growth environment. \n
- Advanced degree in computer science, machine learning, or a related field. \n
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