Full Stack Software Engineer

About LGND

LGND is an early-stage startup revolutionizing geospatial AI infrastructure. We bridge the gap between large Earth observation models and specific application developers, enabling intuitive interaction with geospatial data. Our core mission is to empower decision-makers with rapid insights from vast, complex datasets. As part of our small, dynamic team, you will play a foundational role in building tools that have never existed before.

We re looking for a creative and energetic Full Stack Software Engineer to join our founding product team. In this role, you ll take early-stage ideas and rapidly turn them into functional, interactive demos that showcase the potential of our platform. You ll work primarily in React and Python, interfacing with LGND s APIs, geospatial services, and large-scale AI frameworks — including emerging protocols like Model Context Protocol (MCP).

This is a fast-moving, experimental role designed to help us quickly validate features and use cases. You ll work closely with product and research leads, build lightweight interfaces to our backend infrastructure, and prototype interactions that bring geospatial data and AI results to life — especially through mapping and spatial UI.

This role is ideal for someone who thrives in ambiguity, ships quickly, and has a strong eye for product potential. It s a unique opportunity to help define and shape the frontend of an AI-native geospatial platform before we scale a broader engineering and design team.

This is a hybrid role, with a preference for candidates based in New York, San Francisco Bay Area, or Copenhagen. Remote work is also a possibility.

• Rapid Prototyping:
  Take ideas from whiteboard to working demo in days — not weeks. Build and iterate on new products and features using lightweight frontends and LGND s backend APIs
• Frontend Development:
  Build rich, spatially aware interfaces using React, including map-based UIs (e.g., Mapbox), data visualizations, and lightweight dashboards
• API Integration:
  Work almost entirely against APIs, integrating LGND s services and MCP servers, as well as third-party geospatial services
• Backend
  
  Collaboration:
  
  Write or modify small backend components using Python, especially for internal tooling or lightweight extensions to our existing APIs
• Infrastructure-Aware UI:
  Build frontends that are responsive to real-world compute and data infrastructure constraints — particularly when working with large spatial datasets or ML workflows
• UX Experimentation:
  Help evaluate UX for interacting with embeddings, vector search results, and spatial metadata. Propose new patterns where needed
• Cross-functional Collaboration:
  
  Work alongside AI engineers, backend developers, product leads, and researchers to translate technical workflows into intuitive interfaces
• Speed & Flexibility:
  Adapt quickly in a fast-moving startup environment where priorities evolve and experimentation is encouraged

• Build an interactive map-based UI to demo a new geospatial search capability powered by LGND s vector search API
• Prototype an exploration interface that allows users to define an area of interest, select a model, and query MCP-based search results
• Help build the internal playground for evaluating embeddings and vector comparisons across different model outputs
• Integrate Mapbox maps and other geospatial layers into demo frontends for live user testing
• Collaborate with backend and research teams to refine UI/API contracts and suggest frontend-side enhancements

• Frontend Expertise:
  Deep experience with React, including component architecture, state management, and styling frameworks
• Mapping Libraries:
  Familiarity with Mapbox, Leaflet, or other map tile or rendering libraries. Backend Fluency:
  Working knowledge of Python, especially for integrating with APIs or writing lightweight backend logic
• API Integration:
  Comfortable working with RESTful APIs, JSON payloads, and asynchronous calls
• Database
  
  Experience:
  
  Some experience with relational databases like Postgre
  
  SQL or MySQL
• Rapid Iteration:
  Ability to quickly prototype, test, and revise interfaces…