Description
- Strategically optimized the product’s infrastructure on AWS, resulting in a remarkable cost reduction of over 50% while fortifying network security.
- Improved the product’s availability and fault tolerance through dynamic horizontal scaling on AWS, ensuring uninterrupted service and enhancing user experience.
- Automated integration testing using PyTest, effectively saving over 4 hours of manual testing time in each sprint.
- Asynchronously decoupled individual micro-services and introduced dead letter queues (DLQ) to ensure reliable and uninterrupted operation of the product’s pipeline.
- Developed Python scripts to streamline product installation on customer sites, significantly reducing onboarding time by over 200%.
- Performed a comprehensive revamp of the backend codebase, improving readability, fixing bugs, and enhancing performance by identifying and resolving bottlenecks.
- Actively engaged with potential customers as the lead developer, providing technical guidance and support to drive customer success which increased product adoption by over 20%.
- Led and mentored a team of 3 junior interns in successfully designing, developing, and seamlessly integrating a sophisticated AI pipeline with the product.
- Building a cloud-native version of the product on Kubernetes with GitOps principles, to facilitate easy deployment and management of multiple instances of the product on the cloud.
