The current digital recruitment landscape is heavily mediated by algorithmic parsing technologies, requiring job seekers to submit highly standardized, machine-readable professional documents. Traditional word processors frequently introduce formatting anomalies, while legacy web-based resume builders suffer from constrained data portability and complex backend rendering overhead. This report provides an exhaustive architectural evaluation and operational analysis of "Resume Craft," a contemporary Single Page Application engineered to resolve these inefficiencies. Constructed utilizing React 19, Vite, and Google Firebase v12, the platform facilitates real-time data binding, cloud-synchronized persistence, and purely client-side document compilation. By employing the html2canvas and jsPDF libraries, the system translates the Virtual DOM directly into a downloadable Portable Document Format payload within the local browser environment. A comprehensive system architecture analysis is presented herein, contrasting this serverless, client-side generation paradigm against traditional server-side rendering methodologies concerning computational resource allocation, network latency, and semantic data preservation. The findings indicate that while the Backend-as-a-Service approach affords exceptional horizontal scalability, rapid deployment, and high-fidelity authoring experiences, the reliance on HTML Canvas-based rasterization for document generation introduces a critical operational vulnerability. Specifically, the conversion of text into image matrices severely degrades Applicant Tracking System parsing efficacy, effectively rendering the candidate invisible to recruitment algorithms. The study concludes by proposing hybrid rendering architectures, server-side headless browser integrations, and advanced state management migrations to optimize both infrastructural efficiency and the end-user's employment prospects in highly competitive, artificially intelligent hiring ecosystems.