Bryan Viray Centeno

Lead architecture and development of AI-powered website-building solutions and intelligent agent workflows, integrating generative AI with platform engineering. Built LLM-powered features using Python, TypeScript, and LLM APIs to automate content generation and code assistance, reducing manual development effort. Designed multi-agent workflows with LangChain and LangGraph including supervisor orchestration and tool calling, improving task completion rates. Implemented scalable AI backend services using FastAPI and AWS Lambda for inference and asynchronous processing, reducing API latency, and integrating with WordPress. Architected AWS infrastructure (ECS, S3, RDS, IAM, Docker) with automated scaling and cost optimization, and delivered CI/CD with GitHub Actions and AWS services to reduce deployment time and improve reliability.

Designed and delivered scalable cloud-native applications and enterprise platforms on AWS, focusing on distributed backend architectures, infrastructure automation, and reliable deployments. Developed microservices-based systems using Node.js, Python, and TypeScript supporting high-volume API traffic. Built AWS infrastructure using EC2, ECS, Lambda, RDS, S3, and API Gateway to enable scalable deployments and automated provisioning. Developed RESTful APIs and asynchronous workflow integrations, improving response times. Implemented containerized CI/CD pipelines with Docker, Terraform, and GitHub Actions, reducing deployment time significantly. Enhanced observability and security with CloudWatch, IAM, and AWS Secrets Manager.

Developed and maintained web-based business applications and digital platforms, delivering responsive frontend interfaces, backend APIs, and database-driven solutions. Built full-stack applications using Java (Spring Boot), React, and MySQL, supporting multiple customer-facing portals and internal business management modules. Implemented REST APIs for authentication, transaction processing, and third-party integrations across many application modules. Improved frontend performance through component optimization and efficient asset loading. Optimized MySQL schemas and queries to reduce latency for frequently accessed features. Added automated testing and streamlined deployment workflows, reducing recurring production defects and improving release efficiency.