Summary
Origen is hiring an AI Builder - GIS Data Mining Engineer for a role listed in Shenzhen and Abu Dhabi. The engineer will develop geospatial and spatiotemporal intelligence modules covering data ingestion, indexing, model inference, analytics, and visualization, and turn foundation models, VLMs, and agent technologies into product features. The role also involves cross-functional collaboration, technical design reviews, and mentoring as the team grows. Applicants should have a bachelor’s degree or above, at least two years of software development experience, proficiency in one listed programming language, and experience building a complete system with AI-assisted development tools.
The posting
As published on origen.ae. Pulled from the employer's site and shown as they wrote it.
Position Overview
As an AI Builder - Geospatial Intelligence & Spatiotemporal Data Mining Engineer at Origen, you will contribute to the development of next-generation AI-native spatiotemporal intelligence systems. This role focuses on integrating foundation models, Vision-Language Models (VLMs), and Agent technologies into remote sensing analysis, spatiotemporal data mining, and intelligent situation awareness workflows.
You will work closely with the core team to design and develop key product modules, including data processing, intelligent analytics, model inference, and visualization capabilities, while leveraging AI tools to accelerate product iteration and engineering efficiency.
This role offers the opportunity to work on cutting-edge AI and geospatial technologies and contribute to rapidly evolving products with real-world business applications.
Key Responsibilities
1. Lead the design and end-to-end development of core modules related to intelligent situational awareness and spatiotemporal data mining, covering data ingestion, spatiotemporal indexing, feature extraction, model inference, and visualization interaction;
2. Transform large models, vision-language models (VLMs), and Agent capabilities into deployable product features, including but not limited to intelligent remote sensing image interpretation, multi-source spatiotemporal data correlation analysis, automated situation assessment, and natural language interactive analysis;
3. Work closely with product managers, algorithm engineers, and domain experts to rapidly iterate prototypes and take ownership of final delivery outcomes;
4. Participate in establishing engineering standards and technical architecture decisions, while taking responsibility for technical reviews and mentoring new team members during team expansion.
Candidate Profile
1. Education & Background: Bachelor’s degree or above, preferably in Computer Science, Software Engineering, GIS, Remote Sensing, Artificial Intelligence, or related fields; strong cross-cultural collaboration skills;
2. Engineering Experience: At least 2 years of hands-on software development experience, with the ability to independently deliver complete modules or products;
3. Programming Skills: Proficient in at least one of Python, Java, Go, Rust, or TypeScript, with solid engineering fundamentals and strong code quality awareness;
4. AI Tool Practice: Proficient in using AI development tools such as Claude Code and Cursor as daily productivity tools. Candidates should have independently built at least one complete system using AI-assisted workflows and be able to clearly explain the development process, technical decisions, and efficiency improvements achieved;
5. Learning Ability: Able to quickly understand unfamiliar business domains and rapidly build demonstrable prototypes;
6. Collaboration Skills: Strong communication and coordination skills, with the ability to maintain stable delivery in fast-changing environments and collaborate efficiently with cross-functional teams.
Preferred Qualifications
Candidates with experience in one or more of the following areas will have an advantage:
1. Remote sensing image analysis, including image preprocessing, object detection and recognition, change detection, and semantic segmentation;
2. Spatiotemporal big data analytics, including trajectory mining, spatiotemporal clustering, spatiotemporal indexing (H3, S2, Geohash), and PostGIS;
3. GIS development, including geospatial data processing, map visualization, and 3D scene construction (Cesium, Mapbox, Deck.gl, etc.);
4. Intelligent situation awareness, including multi-source data fusion, event association, situation reasoning, and visualization;
5. Vision-Language Models (VLM), including multimodal model fine-tuning and inference optimization, especially in remote sensing or video scenarios;
6. Spatiotemporal knowledge graphs, ontology modeling, spatiotemporal reasoning, and graph databases such as Neo4j and NebulaGraph;
7. Other related areas such as multi-agent systems, RAG, MCP, and complex workflow orchestration;
8. Active open-source projects, technical blogs, or independently developed products.