Yusuke Doi

Led the development of AI-enabled SaaS applications using React.js, Next.js, Nest.js, and MongoDB; built scalable full-stack products in fast-moving startup environments. Architected responsive frontend systems with SSR/SSG strategies, optimized rendering for performance and SEO across devices. Engineered scalable Node.js backend services and REST APIs to support automation workflows and real-time operational systems. Integrated third-party AI/LLM APIs to orchestrate intelligent workflows and AI-assisted tooling. Built interactive dashboards with real-time telemetry and reporting, implemented efficient state management and modular UI components in TypeScript and Tailwind. Established deployment pipelines with Docker, Kubernetes, GitLab CI/CD, and AWS; strengthened observability and logging. Mentored engineers and collaborated with product, design, and operations teams to prototype MVP features.

Spearheaded development of scalable full-stack platforms using React.js, Next.js, Node.js, and PostgreSQL; supported high-traffic internal tools and operational systems. Architected and optimized dynamic dashboards with real-time monitoring, analytics visualization, and operational reporting. Developed backend APIs and microservices with Node.js and Express.js; designed resilient distributed systems using Kafka and event-driven patterns. Accelerated frontend performance with SSR-aware Next.js architecture, modular state management, and optimized rendering. Enhanced data models and queries in PostgreSQL; integrated Grafana/Prometheus/ELK for observability. Drove productivity by introducing reusable frontend patterns, automation tooling, and AI-assisted development workflows; collaborated closely with product, design, and infrastructure teams. Deployed containerized apps using Docker and AWS, with exposure to Kubernetes concepts. Mentored junior engineers through architecture reviews and

Engineered cloud-native backend services powering Prime Video platform operations across multiple regions. Automated benchmarking and release validation workflows, enabling data-driven decisions and improved platform reliability. Generated and analyzed millions of operational events daily to drive release decisions. Built automation pipelines and distributed tooling to accelerate testing and deployment, reducing manual intervention. Applied computer vision and machine learning techniques to improve benchmarking reliability and failure detection. Collaborated cross-functionally to refine platform requirements and deliver scalable backend solutions.