- Part of newly launched Infa CDIPC team, contributed to Domain Management Cloud Service and Modernization initiatives for shifting control of on-premise customer domains to cloud.- Reduced delays in intercommunication between on-prem and cloud services by introducing an idempotent on-prem service. Got awarded by our respected staff engineer.- Designed and tested upgrade eligibility of on-prem Infa Domains in the cloud, addressing corner cases.- Reduced an artifact's size by 150% by removing redundant dependency libraries, shrinking the installer size.- Introduced automated bash and batch scripts for cloud monitoring process present on-prem, ahead of schedule.- Authored a comprehensive build wiki for CDIPC team, recognized by our Director of Development.- Enhanced a 10-year-old product Infa Developer client tool based on Eclipse OSGI, resolving Priority 0 customer escalations.- Improved model repository load time in Developer client by 20%.- Trimmed $71 monthly EC2 computing cost by disabling an unnecessary feature for a customer.- Collaborated with the Documentation team to document newly created features.- Conducted personal meetings and debugged issues with sibling teams in free time.- Provided quick fixes for graphic issues in Infa Developer Client for users with low vision or photosensitivity.- Detected and reported hard race conditions in parallel product teams working on Oracle RAC failover.- Gained expertise in Spring Boot, TLS, JWT, and logging.- Documented extensive knowledge in a collection of wikis.

- Worked on-site at Cisco Systems India, on enhancing an enterprise product EPNM (Evolved Programmable Network Manager). - Designed, Developed and Maintained services using Java based stack and Spring framework for inventory component.- Solved more than 85 defects as a part of enhancements in the product.

Developed an Android application using Java and Retrofit REST library to contribute end to end for the client CenturyLink. The application helped in notifying the users about their network usage/bandwidth/GPON stability i.e. Gigabit Passive Optical Network Mechanism tracking information. (Jan 2018 - March 2018)Training for Java/JDBC/Hibernate (August 2018 - December 2018)

- Developed a predictive model that analyzes raw public consumption data to forecast passenger flow, optimize train schedules, and enhance the overall commuter experience in the Delhi Metro. - Random Forest was used as an ensemble method that uses multiple decision trees to make more accurate predictions on passenger flow. - Advantages: More robust and accurate than a single decision tree, handles overfitting better, and provides feature importance scores.

Android App Design Training in Eclipse