Nguyen Van Duong

Designed and delivered interactive data annotation tools with Next.js for AI-related workflows, improving usability for large-scale labeling and review processes
Built scalable backend services and APIs that integrated application workflows with AI algorithms, LLM-powered features, and data pipelines while preserving maintainability and clear service boundaries
Led senior-level LLM integration efforts by designing backend services that connected product workflows with large language model APIs, including prompt orchestration, response validation, error handling, and secure integration patterns
Built Al agent capabilities for complex workflow automation, enabling agents to reason over structured application data, trigger backend actions, and support human-in-the-loop review for production reliability
Planned reusable agent-service architecture with clear boundaries between frontend interfaces, orchestration logic, LLM providers, tool execution, and application data layers
Implemented prompt engineering, context management, guardrails, and validation loops to improve LLM output accuracy, consistency, and maintainability across AI-powered features
Collaborated with product and engineering teams to translate AI-agent requirements into scalable full-stack features using Next.js, TypeScript, Nest.js, GraphQL, and MySQL
Incorporated AI-assisted development into daily engineering work by using Claude Code, Cursor, structured prompts, iterative refinement, and critical review of generated code before production use
Guided implementation tasks with clear context, constraints, and validation steps to improve output quality from AI coding tools and reduce rework during development
Added real-time collaboration capabilities that enabled multiple users to work simultaneously and improved team productivity across shared annotation tasks
Optimized frontend performance through code splitting and lazy loading, reducing initial load times and improving responsiveness for data-heavy interfaces
Integrated GraphQL APIs to streamline data access patterns and improve frontend responsiveness across complex application views
Strengthened engineering quality through testing practices, code reviews, and continuous refinement of AI-generated and human-written code

Designed and built a real-time data processing service for analytics using Apache Kafka, Azure Event Hubs, Azure Functions, and Azure Synapse Analytics, enabling efficient handling of large-scale payment and billing data
Provided real-time insights to clients for transaction monitoring, payment analytics, and settlement forecasting
Architected and configured Kafka topics using Azure Event Hubs, applying partitioning and replication strategies to support high availability and optimized throughput for microservices
Led the development of dynamic, responsive single-page applications for payment management and analytics using Angular 14 CLI, Angular Material, and RxJS
Implemented CI/CD pipelines using Azure DevOps Pipelines and GitHub Actions, reducing manual deployment effort by approximately 50%
Provisioned and managed cloud infrastructure using Azure Bicep and ARM Templates to define Infrastructure as Code, ensuring repeatable and consistent deployments across environments
Created and maintained Helm charts for deployment on Azure Kubernetes Service, supporting release versioning, rollback processes, and reliable microservice deployment

Developed scalable full-stack web applications for a digital commerce platform, combining modern frontend interfaces with resilient backend services
Built microservices and backend processes with Laravel and AWS services to support scalable product features and cloud-based operations
Executed server-side rendering with Next.js to improve page performance, search visibility, and maintainability of frontend architecture
Used AI development tools to accelerate implementation of repeatable components, draft service scaffolding, and support faster iteration while preserving engineering standards
Collaborated with product, design, and engineering stakeholders to modernize legacy systems and improve long-term maintainability
Integrated AWS services including S3, DynamoDB, and API Gateway to support reliable infrastructure and service communication
Delivered real-time functionality with WebSockets for live support and responsive user-facing interactions
Contributed to code quality through review, refactoring, and pragmatic architecture decisions aligned with clean software design principles

Engineered secure backend systems using Node.js to support payment processing, transaction reliability, and service scalability
Developed RESTful APIs for transaction handling and authentication with a focus on clean service design and long-term maintainability
Incorporated third-party banking APIs and external services across multiple regional payment workflows
Applied strong engineering judgment to architecture, code structure, and service reliability in systems requiring security and consistency
Executed encryption and backend security controls aligned with PCI DSS requirements and secure software development practices
Improved PostgreSQL queries and backend data access layers to improve performance for transactional workloads
Supported CI/CD adoption with Jenkins and Docker to improve delivery consistency and release quality
Worked closely with cross-functional teams to troubleshoot issues, refine services, and maintain production reliability