• Designed and developed a centralized multi-level feature entitlement and monetization system

• Designed and implemented a feature entitlement platform enabling dynamic multi-level gating,

improving configuration scalability and feature rollout speed by 80%.

• Developed centralized entitlement services in C# ASP.NET Core for shared access across microservices.

• Implemented hierarchical configuration logic supporting subscription tiers and enterprise-level overrides.

• Built an Angular admin console for plan and feature management, reducing configuration time by 60%.

• Designed an LLM-powered customer support automation system for email diagnosis and error resolution

• Integrated Snowflake Cortex LLM with a rule-engine layer and domain-specific prompt tuning to optimize troubleshooting query generation.

• Built MCP servers to orchestrate LLM interactions, Snowflake queries, and internal RPC microservices.

• Implemented guardrails, validation pipelines, and response filtering for reliable troubleshooting.

• StreamScore Analytics and ML Pipeline Enhancements

• Developed filtering with multidimensional aggregates on StreamScore, reducing service load by 30%.

• Migrated StreamScore computation to Snowflake Python UDFs, improving analytics scalability and

reducing report latency by 4–5 seconds.

• Developed and improved user authentication system

• Programmed and tested authentication service with 96% code coverage to handle 10000 requests

per second using Java and transitive authentication protocol.

• Integrated Amazon’s SSO with audible.com reducing repeated logins to improve user experience.

• Fixed and documented redirection logic to authenticate users if not logged in.

• Led the feature launch, fixed post-launch bugs, and held knowledge transfer sessions.

• Identified and improved bugs in the existing system

• Assessed and fixed security vulnerabilities to block approx. 4000 bot attacks per second.

• Identified and fixed bugs in the payments page to support traffic of 1000 requests per second.

• Refactored legacy code violating design principles to help the team follow coding standards.

• Contributed to filling knowledge gaps in documentation and workflow diagrams.

• Improved operational standards across multiple teams

• Led process improvements on handling bug tickets to maintain less than 10 tickets per week.

• Created dashboards to track metrics and alarms to mitigate high-severity bugs.

• Collaborated with 5 different teams to find the patterns in the tickets and fixed recurring bugs.

• Developed web application hosting Setup Guide for new users using Angular8 and TypeScript.

• Rewritten components with improved UI and functionalities to support new features of the Setup Guide.

• Written routing modules and routing guards to allow routing across components and restrict certain routes.

• Built services to handle REST API calls and to help handle error messages from servers.

• Written Angular Pipes to extract and format data from the API response Data Transfer Objects.

• Designed and developed NGRX stores to track and store the states of the API calls and component states.

• Written REST APIs to get data from database objects with Cross-Origin Resource Sharing support using C#.

• Deployed the backend and frontend services on the Azure portal for beta release.

• Developed and tested components to manage server data, user data, and user credentials using Angular8 and TypeScript.

• Created ViewModel observable for the components to trigger store action on user events.

• Designed and built Page and API stores to store the state of the components and API calls respectively using Redux.

• Built Services to handle REST API calls to retrieve and update user, server data from the backend.

• Written unit tests using Jasmine and Karma to test the components and services.

• Updated the SocketLabs Injection API to support timeout functionality and retry on network failure with multiple language support for Java, Python, Go, Ruby, Node.js, PHP.

• Written a Kafka Consumer service using C# to read messages from the topic queue and update the database using Entity Framework Core.

• Built a machine learning model to filter the bad signup requests.

• Wrote Python scripts to load data from S3 bucket, to perform Univariate and Bivariate Analysis to get insights from data and create visualizations to learn data patterns and their correlations.

• Built a linear model to impute missing values through predictions to get better estimates.

• Handled the imbalanced dataset using oversampling method SMOTE and generated synthetic data.

• Wrote Python scripts to fit classification models like Logistic Regression, SVM.

• Used ensemble techniques like Random Forests, Bagging to boost the performance of the model.