Technologist
Current- Ensured EIP(Enterprise Integration Patterns) efficient usage to design and implement standardized solutions for integrating disparate IoT systems/devices/sensors, ensuring efficient communication and data exchange within an enterprise-level IoT offering (CSensorNet).- Leveraged Java, Microservices, Spring, Spring Boot, Hibernate, and JPA to design a highly scalable, modular, and responsive software architecture, enabling its efficient development and deployment- Utilized Kafka to provide a highly scalable and fault-tolerant platform for real-time data streaming and event-driven architecture, facilitating data integration, processing, and distribution across various microservices- Employed Elasticsearch and Kibana to collectively enable real-time data indexing, search, and visualization, empowering users to efficiently explore and analyze large datasets for insights and monitoring.- Incorporated AI/ML patterns like ANN, CNN, Regression, Classification, and Clustering to facilitate tasks such as pattern recognition, predictive modeling, image analysis, anomaly detection, and data organization, enhancing automation and decision-making capabilities.- Added CI/CD (Continuous Integration and Continuous Deployment) pipelines in Jenkins and CircleCI to automate and streamline the process of building, testing, and deploying applications, ensuring faster, more reliable, and frequent releases.- Created Edge computing module (CSensorNetLite) enabling real-time processing and analysis of data closer to the source or device, reducing latency and enhancing responsiveness for the cloud application and services.- Deployed the SaaS ecosystem on AWS to provide scalable, flexible, and cost-effective cloud infrastructure and services for hosting, storing, and managing applications and data.- Training, mentoring, and building multiple cross-functional engineering teams from scratch- Involved in handling technical aspects of various RFP/RFQ/RFI