Ria Bhat

Led critical development and testing initiatives for intent detection and AddSpeakerNotes features, significantly enhancing user experience and system reliability at Microsoft.

• Awarded People's Choice in a company-wide hackathon for an innovative intent detection feature, recognized for significant user experience improvements.
• Led the optimization of OCV and customer feedback mechanisms, implementing multiple updates to improve user experience, including dynamic speaker note integration across various languages and prompt lengths.
• Pioneered and led the end-to-end Slinky testing E2E automation in India, establishing the first automated test implementation for the feature.
• Directed Red team testing and comprehensive logging, metrics, and monitoring for the AddSpeakerNotes feature, ensuring robust functionality and data observability.

Drove the development of new services and critical system enhancements, ensuring robust functionality and efficient resource management for partner integrations.

• Developed and implemented robust validations for a new service from scratch, ensuring seamless launch and integration with external partners.
• Identified and resolved multiple dependency vulnerabilities in code, taking full ownership to enhance system security and stability.
• Engineered new endpoints to support a comprehensive resource creation workflow, improving efficiency and user experience.
• Conceptualized and implemented a new flow to eliminate resource duplication across services, enhancing system efficiency.

Enhanced customer experience and system reliability through proactive issue resolution and feature development for payment and transaction systems.

• Improved customer experience by proposing and implementing ideas for transaction sharing and repeat payments, now actively deployed.
• Identified and resolved a critical connection timeout issue and investigated/fixed a redirect page UI bug, enhancing system stability and user flow.
• Developed a script to analyze logs, accurately documenting occurrence of race conditions for improved system diagnostics and stability.

Delivered significant software enhancements and operational improvements for clients, focusing on search functionality, alert management, and software deployment.

• Developed and deployed a new camera location search feature, significantly improving search efficiency across large areas for 10 key clients.
• Reduced parking ticket alert overflows, optimizing system notifications and improving operational efficiency.
• Enhanced user software experience by creating install and run scripts for software packages, streamlining deployment and setup processes.

Contributed to critical security and performance improvements, optimizing data storage and API latency for internal Amazon systems.

• Reduced security risks by deprecating the storage of "RED" data in S3 buckets, enhancing data protection protocols.
• Improved API latency by 40%, significantly boosting system responsiveness and user experience.
• Stabilized jobs and increased their success rates from 0.82 to 0.89, ensuring higher operational reliability.
• Segregated data on an internal Amazon portal by merchant type, impacting over 1050 merchants and improving data management.

Developed an Amazon Lockers Management System application to enhance locker search capabilities for users.

• Developed an Amazon Lockers Management System application, enabling users to efficiently locate lockers within a specified distance range.
• Designed and implemented the application using Node.js, MongoDB, and Geocode API to provide location-based search functionality.

Awarded for enhancing intent detection feature, recognized for innovative user experience improvements.