S Mohan Email & Phone Number

• Designed and developed a user-friendly dashboard using React.js, enabling vendors to monitor their invoices in real-time.• Implemented AWS Lambda functions to handle data processing and ensure scalability.• Set up a CI/CD pipeline using Jenkins to automate deployment, testing, and monitoring of the application, ensuring rapid and reliable updates. This saved $2 million annually by processing 6000 invoices hourly using DynamoDB. • Integrated with AWS IAM for managing user roles and permissions.• Re-engineered the backend service to use AWS Firehose for streaming audit logs to S3 buckets.• Implemented data processing pipelines to ensure the integrity and availability of audit logs.• Improved service availability and reduced costs through efficient resource utilization and better data management.• Developed backend services to execute integration tests and process results, leveraging REST API calls for seamless integration between services.• Automated the testing pipeline using CodePipeline, ensuring continuous integration and delivery.• Reduced production bugs by 25% through comprehensive and automated end-to-end testing.• Developed user interfaces to facilitate the two-person rule mechanism, ensuring that sensitive operations required dual authorization.• Built backend services to enforce the two-person rule, integrating with AWS IAM for role and permission management.• Implemented workflows using AWS Lambda to manage approval processes and ensure compliance with security policies.• Enhanced data security by reducing the risk of unauthorized access through dual authorization.• Implemented multi-threading in Java to optimize the synchronization of LDAP groups and the execution of DJS jobs.• Reduced execution time from 10-15 hours to 40 minutes, resulting in an 80% time saving.• Proficient in utilizing AWS CloudWatch logs and insights for logging, monitoring, and debugging purposes, enabling efficient troubleshooting and analysis of system behavior.

• Implemented features that increased conversion rates by 15% and product discoverability by 20% through an optimized checkout process and improved search functionality using • Reduced page load times by 30%, significantly enhancing the overall user experience.• Designed and implemented user-friendly registration and onboarding interfaces using React.js, ensuring a seamless sign-up process that attracted new users.• Developed scalable APIs using Node.js and Express.js to handle user registrations and profile management, integrating with AWS Cognito for secure user authentication.• Deployed the application using Docker and Kubernetes to ensure scalability and reliability, capable of handling increased traffic as membership grew.• Implemented GraphQL to efficiently fetch and deliver personalized data from the server to the client, ensuring a responsive and tailored user experience.• Created dynamic and personalized user dashboards using React.js, where members could view customized content, recommendations, and exclusive offers based on their preferences and activity.• Built data pipelines to analyze user behavior and preferences, using AWS services such as Lambda and S3 to process and store analytics data• Developed interactive features like event sign-ups, reminders, and exclusive content access within the Nike+ membership portal, which increased a 20% of member participation.• Built and integrated APIs to manage event registrations and participant data, ensuring secure and efficient handling of member information.• Improved inventory accuracy by 25% and reduced order processing times by 40%, leading to faster fulfillment and higher customer satisfaction. Decreased logistic costs by 15% through optimized inventory management.• Implemented JMS for notifications and testing with JUnit, Mock cases. Wrote JUnit Test cases for Spring Controllers and Web Service Clients in Service Layer using Mockito.

• Developed a comprehensive management dashboard for F5's Web Application Firewall, allowing administrators to monitor, configure, and manage WAF rules and policies in real-time.• Developed data visualizations using D3.js to display traffic patterns, security events, and threat analytics.• Developed RESTful APIs to interact with the WAF configuration and monitoring services, ensuring secure and efficient data exchange.• Utilized AWS Lambda for event-driven processing and AWS S3 for scalable storage solutions.• Built a cloud-native application to configure and manage F5's load balancing solutions, enabling users to deploy and optimize load balancers across multiple cloud platforms.• Created a sleek and intuitive UI for configuring load balancer settings, monitoring performance, and managing traffic policies.• Implemented features for real-time monitoring and alerts, providing administrators with timely insights and notifications.• Developed GraphQL APIs to provide flexible and efficient data querying capabilities for load balancer configurations.• Implemented backend services using Spring Boot to manage load balancer instances and handle orchestration across different cloud environments.• Created a performance monitoring tool for F5's ADC solutions, providing detailed analytics and insights into application delivery performance and health.• Developed interactive dashboards and reports to visualize ADC performance metrics, including throughput, latency, and error rates.• Implemented drill-down capabilities to allow users to investigate performance issues and identify root causes.• Implemented caching strategies using Redis to optimize data retrieval and improve response times.• Created RESTful APIs to expose performance data and support integration with other monitoring tools and systems.• Developed backend services to aggregate security data from various sources, processing and storing it in Elasticsearch for fast search and analysis.

• Implemented user-friendly interfaces for flight, hotel, and car rental bookings, ensuring a seamless booking experience.• Integrated real-time data updates using WebSockets to show live availability and price changes.• Enhanced the search functionality with filters and sorting options to help users find the best deals quickly.• Developed RESTful APIs to handle booking queries, process payments, and manage user reservations.• Implemented server-side logic to handle real-time updates and notifications using AWS Lambda and WebSockets.• Designed and implemented a user profile dashboard where users can view and manage their personal information, bookings, and loyalty points.• Create intuitive interfaces for earning, tracking, and redeeming loyalty points.• Developed backend services to manage user profiles, including authentication, data storage, and profile updates.• Implemented GraphQL APIs to fetch user profile and loyalty program data efficiently.• Used Redis for caching frequently accessed data to improve performance.• Created a recommendations section on the homepage and user dashboard, showcasing personalized travel suggestions.• Implement interactive UI components that allow users to filter and explore recommendations.• Developed backend algorithms to analyze user behavior and preferences, generating personalized travel recommendations.• Use Elasticsearch for fast search and retrieval of recommendation data.• Designed and integrate a chatbot interface within the travel booking platform, providing users with immediate assistance.• Developed backend services to manage chatbot interactions, leveraging AWS Lex for NLP capabilities.• Implemented integration with booking and support systems to provide relevant and accurate responses.• Used MongoDB to store conversation logs and user interactions for continuous improvement of chatbot responses.

• Utilized React.js and Redux for building a dynamic and responsive UI, presenting features such as real-time device control and energy consumption monitoring.• Focused on intuitive design with clear navigation and feedback mechanisms, enhancing the user's ability to interact with home automation features seamlessly.• Integrated with backend services via RESTful APIs, facilitating real-time updates and data synchronization.• Using Node.js and Express.js handled requests from the frontend and manage data flow between various components.• Used on MongoDB for storing user preferences, device configurations, and automation schedules efficiently.• Utilized AWS Lambda for executing serverless functions, enabling scalable and cost-effective backend operations.• Built recommendation interfaces using Vue.js and HTML/CSS, presenting personalized automation suggestions based on user behavior and preferences.• Developed recommendation algorithms using Python and Flask, analyzing user data and behavior patterns to generate personalized automation suggestions.• Utilized Elasticsearch for indexing and querying user data efficiently, enabling fast and accurate generation of automation recommendations.• Implemented Kafka for real-time data processing, ensuring timely delivery of recommendations based on user interactions.