Work Experience
Nokia, Boston, MA.
- Security Software Developer Co-op (May 2022 - Dec 2022)
- Developed extensions for the Customized IAM solution based on the OpenSource Keycloak project.
- Updated Helm charts for the IAM project for new releases.
- Built the flow and created an application for the logging functionality in the latest release.
Kaleidofin India Private Ltd, IIT Madras Research Park, India.
- Software Development Engineer II (Sep 2019 - Aug 2021)
- Migrated all monolithic applications into a microservices using the best application design patterns from Spring Framework ecosystem.
- Implemented the best in class technology to monitor and alert the developers in case of any failure or scaling issues in the Production Infrastructure 24/7.
- Played a crucial part in Migrating the whole microservies to a high scalable and availability 99.99% platform with Kubernetes and Docker containers.
- Worked on revamping the Android app codebase to meet the new Android 10 and 11 version updates and also added UI changes in the Application.
Next Education India Private Ltd, Hyderabad, India.
- Research and Development Engineer (June 2017 - July 2019)
- Designed a mechanism to scale the applications smoothly and cost effectively (upto 35%) and also to meet the growing requests per minute by our 12M customers.
- Worked on implementing the rate limiting setup and firewall protection for all the applications in the Infrastructure to prevent from DDOS attacks.
- Designed and developed the pipelines for sending bulk mobile messages and Emails to the teachers, students and parents by using the asynchronous message queues.
- Developed backend apis in a microservice for Subscription based video delivery platform
- Worked with DevOps teams to secure the AWS Access keys for mitigating potential security threats.
- Worked on the Nightly Shutdown of the Dev, QA, Pre-Prod Environments for Cost Optimizations.
Cappius Technologies(Anblicks Pvt Ltd), Hyderabad, India.
- Data Scientist Intern (May 2016 - July 2016)
- Developed a Computational model for Customer churn analysis and Insurance claim prediction by using the data and Machine learning techniques with an accuracy of 93.4% and 90.7% respectively.
