Dhanush Raju

I’m Dhanush, a passionate Full Stack and DevOps Engineer with hands-on experience across the entire software

lifecycle. I thrive at the intersection of software engineering, infrastructure, and automation, consistently delivering reliable, scalable, and maintainable solutions.

What I Do:

• Develop full stack web applications using technologies such as React, Node.js, C#, and .NET
• Design and implement RESTful APIs and work with both relational and NoSQL databases
• Build and maintain CI/CD pipelines using GitHub Actions, Jenkins, and GitLab CI
• Containerize applications with Docker and orchestrate deployments using Kubernetes
• Manage and provision cloud infrastructure (AWS, Azure, GCP) using Infrastructure as Code (IaC) tools like Terraform

What I Bring:

• A DevOps mindset focused on automation, scalability, and system reliability
• Proven experience in agile, cross-functional development teams
• A problem-solving approach rooted in thoughtful design and clean, maintainable code
• A commitment to continuous learning and staying current with evolving technologies

AI-Based Dynamic SQL Query Generator & Chatbot
Natural Language to SQL → Database → Chat Response

Overview:
Developed an AI-powered chatbot system that enables users to submit natural language queries, which are translated into dynamic SQL Server queries, executed securely, and returned as chat-based responses.

Key Responsibilities & Features:

• Integrated Azure OpenAI to convert user prompts into dynamic SQL queries compatible with SQL Server
• Executed AI-generated queries with built-in validation to prevent errors and mitigate SQL injection risks
• Designed real-time chat response flow using OpenWebUI for frontend interaction
• Utilized database metadata for context-aware query generation
• Implemented context tracking to support follow-up prompts within the same conversation
• Automated backend workflows using n8n for query processing and response handling
• Developed and consumed REST APIs to integrate components and streamline interactions

Tech Stack:
Azure OpenAI, SQL Server, Node.js, JavaScript, REST APIs, n8n, OpenWebUI

Impact:
Enabled non-technical users to explore and analyze data through natural language, significantly improving data accessibility and reducing reliance on manual SQL writing.

AI-Powered Internal Chatbot System
Powered by MCP Server, n8n Automation, and OpenWebUI

Overview:
Developed an AI-driven chatbot that delivers context-aware responses based on internal organizational data. The solution integrates a custom MCP server for secure data access, n8n for workflow automation, and OpenWebUI as the user interface.

Key Responsibilities & Features:

• Integrated LLMs (e.g., Azure OpenAI or local models) with internal data sources for intelligent, real-time responses
• Utilized MCP server to securely fetch, filter, and process internal documents and databases
• Designed n8n workflows for task automation, API routing, and event-driven triggers
• Implemented a chat-based frontend using OpenWebUI for seamless user interaction
• Engineered prompts and context retrieval strategies for accurate, domain-specific output
• Enforced role-based access control and logging for secure data handling and traceability
• Set up monitoring tools to track usage metrics, performance, and model accuracy

Tech Stack:
MCP Server, n8n, OpenWebUI, Azure OpenAI (or local LLM), JavaScript, Node.js, REST APIs

Impact:
Improved employee productivity by enabling natural language access to internal systems and documents. Reduced reliance on IT and manual data retrieval through AI-powered automation and intuitive chat-based interaction.

Dynamic UI Generator Using AI
Natural Language to Dynamic Frontend (Azure OpenAI, React.js)

Overview:
Designed and developed a web-based platform that dynamically generates user interfaces based on natural language prompts, leveraging Azure OpenAI for prompt interpretation and UI generation.

Key Responsibilities & Features:

• Integrated Azure OpenAI (GPT models) to interpret natural language inputs and generate structured UI component definitions
• Built a dynamic rendering engine in React.js to create forms, buttons, and layouts in real time
• Enabled conversational input such as “Build a form with name, email, and submit” to generate fully functional UI instantly
• Developed prompt tuning and output validation mechanisms to ensure consistent and accurate UI generation
• Ensured secure input handling and output rendering to prevent injection attacks and runtime failures
• Implemented a responsive UI engine with adaptive layouts and real-time rendering logic

Tech Stack:
Azure OpenAI, React.js, Node.js, Express.js, Tailwind CSS, Figma (for prototyping)

Impact:
Accelerated frontend development and prototyping by allowing non-technical users to generate UI components through natural language. Enabled faster MVP iterations and streamlined idea-to-interface workflows.

Transport Management System (TMS)
Quasar (Vue.js) Frontend | C# (.NET) Backend | SQL Server | 200+ Active Clients

Overview:
Led the development of a full-featured Transport Management System to automate and streamline logistics operations for over 200 active clients. The platform supports complete transport workflows from order creation to dispatch and reporting.

Key Responsibilities & Features:

• Designed and implemented a responsive frontend using Quasar Framework (Vue.js) for user-friendly interactions
• Developed scalable backend services in C# (.NET) to manage complex transport workflows and business rules
• Built and optimized SQL Server databases for high-performance data operations and real-time analytics
• Managed key modules including:
  Shipment Scheduling
  Route Optimization
  Carrier & Vehicle Management
  Invoice & Payment Tracking
  Client-Specific Customizations
• Integrated with external ERP and third-party logistics platforms via APIs
• Provided ongoing support, bug fixes, and live deployment management across environments
• Monitored application health, optimized system performance, and ensured high availability

Tech Stack:
Frontend: Vue.js with Quasar Framework
Backend: C# (.NET)
Database: SQL Server
Tools: Git, Postman, Azure DevOps

Impact:
Improved logistics efficiency across a large client base by reducing manual operations, enhancing real-time visibility, and delivering data-driven insights. Enabled clients to scale operations while maintaining control and traceability.