Job Description

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.

Role Summary

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.

Key Responsibilities

• 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.
  
  

Scope of Work: First 3 Months

• 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.

Requirements

Required Technical Skills

• 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 PostgreSQL or MySQL.
• Rapid Iteration: Ability to quickly prototype, test, and revise interfaces with minimal supervision.
• Git & CI/CD: Comfort with version control workflows and basic CI/CD tooling (e.g., GitHub Actions).
• AI/ML Curiosity: Interest in AI/ML systems, particularly geospatial foundation models and vector embeddings (no prior experience required).

Note: Even if you don't fulfill all the criteria, you are encouraged to apply. We welcome applicants from diverse backgrounds and nontraditional paths.

Preferred Experience

• Prior experience in early-stage startups or prototyping environments.
• Exposure to geospatial data and formats (GeoJSON, tilesets, raster data).
• Familiarity with Model Context Protocol or retrieval-augmented generation workflows.
• Experience with visualizing model outputs, embeddings, or ML metrics in frontend apps.
• Comfort designing UIs for non-technical users or analysts.
  
  

Non-technical Skills

• Self-Starter: Comfortable taking initiative, scoping work independently, and managing ambiguity.
• Creative & Curious: Enjoys experimenting with new interfaces and technologies.
• Product-Oriented: Focused on end-user experience and delivering usable value quickly.
• Collaborative: Works well across technical and non-technical stakeholders.
• Flexible & Adaptable: Thrives in environments with competing priorities and shifting context.
  
  

Benefits

Benefits & Cultural Values

At LGND, we prize:

• Humility: Value collaboration and learning from others.
• Integrity: Uphold honesty and transparency.
• Effectiveness: Focus on what works and deliver results.
  
  

Benefits

• Competitive salary based on experience and location
• Equity options in a high-growth early-stage startup
• Health care and 401k
• Flexible work arrangements (hybrid/remote)
• Opportunity to shape LGND’s technology and company culture
• Work on cutting-edge problems in geospatial AI with real-world impact
  
  

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