Software Engineer, Applied GenAI Apps - AI Geospatial Assistant team

<div class="content-intro"><p><strong>Welcome to Planet. We believe in using space to help life on Earth.</strong></p> <p>Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud-based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one.</p> <p>Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world’s toughest obstacles.</p> <p>As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains.</p> <p>We have a people-centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world.</p> <p>Planet is a global company with employees working remotely world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands.</p></div><p><strong>About the Role:</strong></p> <p>Planet’s mission is to image the entire world every day, making global change visible, accessible, and actionable. We are at a critical inflection point: moving from broad AI research to a delivery-focused "productization" model. To drive this, we are building a new product group focused on launching an AI Geospatial Assistant that transforms how our customers interact with global imagery to solve high-stakes problems in forensics and daily change detection.</p> <p>Our goal is to make these complex insights accessible through an intuitive interface that requires zero user training. Operating with a zero-to-one startup mindset, this team prioritizes weekly learning velocity and customer-driven graduation criteria to move rapidly from private alpha to general availability.</p> <p>While AI has enabled software engineers to more easily flex into traditional practice areas like front and back end we would like this role to be more focused on front end than not. You will work with a design lead to be an advocate for the user experience. You will solve the critical "Map-Text Disconnect" by making our global imagery an active, interactive participant in the AI conversation. Your work ensures that natural language insights are always anchored by visual evidence, transforming the solutions into a trusted, intuitive, and "wow"-inducing problem-solving tool for experts and novices alike.</p> <p>This is a full-time, hybrid role which will require you to work from our San Francisco office 3 days per week.</p> <p><strong>Impact You'll Own:</strong></p> <ul> <li>Lead Full Stack AI Web App Development: Take ownership of the user interface and user experience for our new AI-powered chat application, ensuring a highly intuitive, responsive, and visually engaging experience.</li> <li>Collaborate with AI Researchers: Work closely with our AI Research Team to understand their models, workflows, outputs, and emerging capabilities translating complex analytical results into clear, actionable, and visually rich information for end-users.</li> <li>Implement "Interface Advantages": Develop a side-by-side map and chat layout that lowers the barrier to entry for novices while providing deep analytics for GIS experts.</li> <li>Build Trust through Transparency: Integrate visible branding, data badges, and clickable citations to verify that AI-generated answers are grounded in real Planet imagery.</li> <li>Develop Dynamic Visualizations: Create exportable "before and after" graphics, charts, and time-series animations that translate AI insights into actionable evidence.</li> <li>Experience with cloud platforms (e.g., AWS, GCP, Azure) and deploying appl ... (truncated, view full listing at source)