Software Engineer, Applied GenAI Apps - AI Geospatial Assistant team

Planet•San Francisco, CA

12h•Hybrid

About The Position

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. 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. 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. This is a full-time, hybrid role which will require you to work from our San Francisco office 3 days per week.

Requirements

4+ years of experience as a Full Stack or Frontend Engineer, with expertise in modern frameworks like React or Vue.
Bachelor’s Degree in computer science or equivalent field.
Enthusiasm for working in an AI forward development flow. You naturally integrate AI-assisted tools into your workflow to drive your own productivity and enjoy being part of a team that treats AI as a core collaborator in the development lifecycle.
Proficiency of mapping libraries such as Mapbox GL JS or Leaflet.
Experience building streaming UI/UX for LLMs and LLM chat interfaces into production-grade web applications.
Deep empathy for UI/UX principles, focused on democratizing access to complex satellite data for non-technical users.

Nice To Haves

Experience designing dual-mode interfaces (e.g., "Explore" vs. "Analyze") to cater to different user intents.
Prior experience in geospatial visualization for investigative journalism, government compliance, or environmental monitoring.
Prior experience working with AI/ML teams or integrating AI models into production applications, especially chat interfaces and agentic workflows
Strong experience with data visualization tools like D3.js or Plotly.
Experience with "Human-in-the-loop" (HITL) UI design.

Responsibilities

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.
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.
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.
Build Trust through Transparency: Integrate visible branding, data badges, and clickable citations to verify that AI-generated answers are grounded in real Planet imagery.
Develop Dynamic Visualizations: Create exportable "before and after" graphics, charts, and time-series animations that translate AI insights into actionable evidence.
Experience with cloud platforms (e.g., AWS, GCP, Azure) and deploying applications in a cloud environment.
Optimize Performance: Ensure that "slippy map" transitions and high-resolution satellite imagery loading remain performant and seamless, even when handling complex data overlays under high user demand.
Engineer Fluid AI Interactions: Architect sophisticated frontend/backend communication patterns (eg. through use of web sockets) to manage high-latency AI operations. You will ensure the UI remains "alive" and transparent by implementing real-time agent status updates, streaming text responses, and progressive data rendering.
State Management for Multi-modal Conversations.