27th Campus Recruitment - GIS R&D Engineer (Spatial Intelligence)

Job Responsibilities Develop GIS applications for government scenarios such as urban governance, digital government, and emergency command—implementing map service integration, spatial data visualization and querying, layer management, map annotation, thematic rendering, and advanced features like trajectory, heat map, and aggregation visualizations. Participate in integrated 2D/3D visualization and custom project development, designing, implementing, and delivering GIS functionality aligned with client business needs. Handle spatial data development tasks, including data ingestion, spatial querying and statistics, map/tile/feature service publishing, feature service consumption, and spatial indexing. Conduct front-end/back-end integration, collaborate with product and delivery teams, and support end-to-end GIS module development and operations (data, services, and UI). Explore and implement AI/LLM-enhanced capabilities in GIS products—e.g., natural language map search, intelligent Q&A for urban governance incidents, map metric interpretation, trajectory and heat map trend analysis, and automated spatial analysis reporting. Track advancements in GIS, spatial databases, and AI engineering; build reusable, maintainable engineering assets; and continuously improve product experience. Qualifications Expected graduation in 2027 (Master’s preferred); majors in Computer Science, Software Engineering, Geographic Information Science, Surveying/Geomatics Engineering, Remote Sensing, Data Science, or related fields. Exceptional Bachelor’s candidates with strong GIS project experience or high-quality engineering practice may be considered. Minimum GPA of 3.0/4.0 or top 50% in class—though emphasis is placed more on project work, code quality, and learning potential than grades alone. Solid understanding of core GIS concepts: coordinate systems, projections, vector/raster data, spatial relationships; and foundational mechanisms: map/tile/feature services, spatial indexing. GIS majors must demonstrate programming skills; CS majors must grasp core GIS concepts. Proficiency in at least one mapping framework/platform (e.g., OpenLayers, Cesium, Leaflet, ArcGIS, SuperMap, GeoServer); experience developing features such as layer management, spatial querying, annotation, thematic rendering, and trajectory/heat map/cluster visualizations. Strong coding skills in at least one language (Java, C#, C++, JavaScript); familiarity with J2EE or common web architectures; ability to perform full-stack integration and API interfacing; experience with MySQL or Oracle (schema design, indexing, stored procedures); Git collaboration; and basic knowledge of Linux, Docker, and deployment workflows. Basic understanding of LLM, Prompt Engineering, RAG, and Function Calling/Tool Use concepts; awareness of data security, on-premise deployment, and restrictions on transmitting sensitive government data over public networks; willingness to continuously learn AI engineering practices. At least one full-cycle project in GIS/WebGIS or spatial data—able to clearly articulate data sources, map services, front-end/back-end implementation, database design, or spatial analysis methodology, as well as personal role, technical decisions, and trade-offs. Skills in requirement translation (converting government business needs into map features, data models, and UI/UX), problem diagnosis (isolating issues across data, services, rendering, and API layers), and cross-functional collaboration; product awareness around map readability, query performance, and user experience; and genuine interest in government GIS applications. Preferred Qualifications Experience with integrated 2D/3D visualization, spatial analysis, PostGIS, or remote sensing/planning-related projects; Proficiency in Spring Boot, Vue/React, with experience in API design, performance optimization, or project delivery; Practical experience in intelligent Q&A, knowledge base retrieval, natural language interaction, RAG, or Agent demos; Awards in WebGIS, spatial analysis, or urban governance data application competitions, or high-impact open-source contributions; Published papers in relevant fields or verifiable high-quality internship outcomes.