Steve is an AI career coaching platform that turns a resume and insights from an AI-enabled chat with a user into a personalized skill gap report and upskilling roadmap. The platform suggests a personalized course plan, supports continuous learning, and helps shape the user’s career trajectory. Steve is built around schema-constrained JSON artifacts and a configurable career-tree ontology. The system compares confirmed skills against role-specific requirements, prioritizes gaps (critical/important/beneficial), and translates the analysis into embedding-based queries over the course index. Steve has three personas (Interview Coach, Resume Evaluator, and Career Coach) that provide concise feedback tailored to the user’s goals and context. Steve also supports speech Input/Output (I/O) via Whisper-based speech-to-text and a dual-voice text-to-speech layer, enabling users to talk to Steve. The platform offers flexible adaptability across institutions, enabling them to configure deployments by substituting their own ontologies and course catalogs. Our demo uses STEM trajectories as a case study, but the pipeline is domain-agnostic by design. Users can edit inputs, check speech recognition accuracy, and observe consistent updates, illustrating a reproducible, human-in-the-loop pattern for deploying LLMs in career guidance. Steve is currently in its alpha stage and available for demonstration.