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American Forests Logo

Full Stack Engineer

American Forests

$80,000 - $110,000
Aug 29, 2025
Remote, US
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American Forests is looking for a mid-level Full Stack Engineer to join their GIS & Data Science team to build impactful tools focused on reforestation and equitable access to trees and the benefits they provide.

Requirements

  • 3+ years of full-stack software engineering experience, building production applications
  • 2+ years of experience with JavaScript, NodeJS, and React (similar component-based frameworks considered)
  • Proficiency implementing APIs using RPC, REST or similar
  • Experience with containerization and deploying backend services directly to a cloud provider or using a third-party PaaS provider (we use AWS, Flightcontrol).
  • Familiarity with relational databases, ORMs, and schema design (we use PostgreSQL and Prisma)
  • Proficiency with Git, build tools, and testing. Familiarity with CI/CD pipelines
  • Experience with Linux/Unix command line tools for deployment, debugging and system management

Responsibilities

  • Design, develop, and test individual web services, APIs, and application components
  • Build user interfaces using React, Mapbox, and other open source libraries
  • Contribute to lightweight data processing workflows for ETL operations and event-driven transformations
  • Contribute to specifications and architectural decisions
  • Help address scaling, performance, and usability challenges through established best practices and thoughtful problem-solving
  • Write maintainable, reusable code with comprehensive pull requests, tests, and documentation
  • Work with cloud-optimized data formats including Parquet, FlatGeobuf, and PMTiles

Other

  • Experience working with remote teams
  • Bachelor’s degree or equivalent combination of education, training, and experience
  • An interest in using other languages when projects require it (e.g. Python)
  • Experience with geospatial tools and libraries.
  • Experience working on data pipelines that ingest, process or publish data at larger scale (tens to hundreds of GB).