Geospatial SW Engineer

About Mitti Labs:

Mitti Labs is a climate-tech startup dedicated to transforming the rice industry by supporting smallholder farmers in adopting sustainable practices. Our mission is to bring AI and satellite technology into traditional rice farming, reducing methane emissions while improving farmer livelihoods.

Backed by NASA-supported science and a strong ecosystem of partners, we work with global corporations to help them achieve their net-zero goals through verified, high-quality carbon credits. Our initiatives include launching a 40,000 farmers project in Telangana and Andhra Pradesh and reducing air pollution from stubble burning in Punjab.

Our customers — including Fortune 500 companies and leading agri-businesses — trust Mitti Labs to deliver measurable impact across climate, food systems, and sustainability.

We are a team of 30+ data scientists, agronomists, engineers, and operators, including leaders in NASA’s SAR program, with decades of expertise in remote sensing and GHG modeling.

Role Description:

• Design, build and maintain geospatial data infrastructure and scalable pipelines
• Automate workflows, complex data structures, and data handling on the cloud
• Support data scientists, crop modelers, field agents / Ops, and MRV products with geospatial application development using best practices

• 5+ years experience in scientific programming (Python, C/C++), software engineering, and building/maintaining geospatial data science infrastructure
• Familiarity with STAC and Cloud-Native geospatial assets handling and pipelines
• Experience with AWS (or GCP equivalent), serverless architectures (Lambda, Step Functions), containerization (ECS, EKS), storage (S3)
• Experience with open source tools, common data formats (GeoTIFF, NetCDF, COGs, Geojson) and frameworks / libraries (GDAL, GeoPandas, Rasterio, Xarray, Zarr, PyTorch)
• Software containerization, command-line and user interface experience to run programs
• Experience with continuous integration and automated test frameworks
• Basic knowledge/interest in remote sensing, LLMs, simulation models
• Comfortable working with agile data scientists, high-growth environments with rapid iteration and evolving priorities, cross functional teams, version control, and ticketing