GIS-based utility and site data platform for construction planning
CivilGrid aggregates utility, environmental and geotechnical GIS layers into a site-intelligence product for infrastructure and construction teams, built on a PostGIS, GeoPandas and ArcGIS stack with AWS Bedrock in the mix. Hiring is accelerating and tilts toward sales and product rather than engineering, and job posts cite a missing sales playbook and solutions materials, pointing to an early-stage push to build a repeatable enterprise go-to-market motion.
CivilGrid is a privately held company headquartered in San Francisco, CA, with 11–50 employees. It compiles and curates utility, environmental and geotechnical site datasets, sourced in part through relationships with local utilities and public agencies. Its customers include developers, engineers and construction firms that use the data for due diligence, utility research, risk identification and construction planning. The product runs on a web stack of React, Node.js and TypeScript over PostgreSQL/PostGIS on AWS, with GIS tooling such as ArcGIS Pro, QGIS and ArcPy and CAD formats like AutoCAD and MicroStation.
CivilGrid uses GIS tools (ArcGIS Pro, QGIS, ArcPy), Python with GeoPandas, PostgreSQL/PostGIS, React, Node.js, TypeScript and Go, deployed on AWS with Docker, Kubernetes, ECS and RDS, plus AWS Bedrock.
Yes. CivilGrid's hiring is accelerating and weighted toward sales and product, with a senior- and director-heavy mix, all based in the United States.
Job posts point to multi-year enterprise agreements, government pilot programs, verified utility data maintenance, digitizing non-spatial datasets, and designing interfaces for dense spatial data.
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CivilGrid's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.