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Planet designs, builds, and operates the largest constellation of imaging satellites in history, delivering empirical geospatial data via a cloud-based platform to commercial, environmental, and humanitarian sectors. As a Solutions Architect I on the Professional Services team, you will work with customers to understand their problems and architect solutions that drive long-term value using Planet's satellite imagery and geospatial technologies.
You will architect, design, pilot, and operationalize solutions by transforming customer requirements into robust technical architectures aligned with business and technology strategies. You'll deliver workshops, tailored demo applications, and workflows, designing user experiences for solution prototyping. Acting as a technical lead in solution development teams within Agile environments, you'll collaborate with project managers and software engineers to build customer solutions.
Your responsibilities include supporting pre-sales and customer expansions through solution ideation and design, leveraging remote sensing, geospatial, and geoinformatics knowledge alongside AI, machine learning, image processing, and geo-programming expertise. You'll liaise with cross-functional stakeholders including product owners, technical project managers, and satellite engineers to architect optimal solutions. You'll also collaborate with sales, marketing, business development, and proposals teams on large civil government and commercial project bids.
You'll own the customer success lifecycle from scoping and discovery through project execution and delivery, champion Planet's products through training and conference presentations, and engage with the Education and Research program to source novel applications and insights.
Required: 4+ years in technical geospatial or remote sensing roles; Bachelor's degree in GIS, Computer Science, Remote Sensing, Geography, or related field; strong Python programming for geospatial applications; experience with solution design, requirement gathering, and prototyping; proficiency with QGIS, ArcGIS, GDAL, ENVI, or similar tools; familiarity with cloud environments (GCP, AWS, Azure); Agile team experience; ability to run workshops and training sessions. Preferred: advanced machine learning experience with geospatial data, industry knowledge in forestry, natural disasters, sustainability, or agriculture, and experience with AI productivity tools like Streamlit.
