• Built and scaled AI-powered capabilities within Power Apps, focusing on backend systems, infrastructure, and data pipelines to enable intelligent

features and data-driven decision-making, improving performance and user experience across the platform.

• Designed and implemented a scalable telemetry API using C#, Node.js, TypeScript, and React, capturing user interaction signals across AI features,

contributing to approximately 40% increase in user retention and actionable insights for product strategy.

• Led end-to-end development of tenant-level AI feature controls, architecting new infrastructure and APIs that enabled granular admin governance,

mitigated security risks, and saved around $2M annually in potential privacy or compliance violations.

• Architected and delivered a modern survey platform on Microsoft 365, migrating from legacy Dynamics 365, rebuilding eligibility logic, authentication,

and telemetry pipelines, resulting in over 50% increase in user feedback collection and engagement metrics.

• Owned AI feedback and analytics pipelines, developing dashboards and insights that informed product decisions, improved feature adoption across

Power Apps, and enhanced monitoring of AI feature usage, errors, and operational performance.

• Utilized a diverse tech stack including C#, .NET, Node.js, TypeScript, React, Next.js, and Microsoft Azure, driving scalable, maintainable solutions while

collaborating across teams to deliver high-impact AI and platform innovations.

• Engineered an innovative automation bot to streamline online meeting processes across MS Teams, Cisco Webex, Google Meet and Zoom, enhancing efficiency of joining, recording and leaving meetings.

• Developed the solution in Python, using Flask for the server and Selenium WebDriver for the automation, achieving a 33% reduction in manual meeting management tasks.

• Adopted Agile methodologies, specifically the Scrum model, to dynamically adapt to project requirements, leading to a 25% improvement in sprint delivery times.

• Contributed to the development and enhancement of a Java based Spring Boot API for the university’s online portal, resulting in a 15% increase in backend performance and scalability.

• Extended unit testing coverage with Junit for new and existing API endpoints, achieving over 90% code coverage and ensuring robust application reliability.

• Collaborated on the development of the new student module on the front-end using React.js and Next.js, which improved the web portal’s student engagement and influx by more than 25%.

• Architected Customer Analytics Platform using Python Flask microservices for large-scale event processing, collaborating with product and design

teams, ensuring low-latency, reliable customer engagement tracking, seamless interactions, and highly scalable, secure, fault-tolerant system.

• Engineered asynchronous Support Ticket Event Processing services using Redis, AWS ElastiCache, and connection pooling, optimizing microservice

communication, reducing API latency by 15%, enabling high-throughput, event-driven processing for millions of concurrent tickets efficiently.

• Designed fault-tolerant microservices with circuit breakers, service discovery, load balancing, and backend WebSocket support in Python, handling

50K+ concurrent events, improving platform scalability, resilience, and responsiveness for real-time agent-customer interactions across the system.

• Implemented secure PostgreSQL database solutions, optimizing schemas, indexing, and queries, enforcing encryption-at-rest and in-transit, with

dynamic RBAC and JWT, reducing authentication incidents by 10%, ensuring data security, compliance, and efficient customer ticket management.

• Built React dashboards for Operational Insights, integrating REST APIs and WebSockets, delivering real-time visualization of customer interactions,

campaign performance, support metrics, enabling informed operational decisions, improving monitoring efficiency, and actionable insights by 17%.

• Integrated observability and monitoring using AWS CloudWatch and Grafana, tracking system health, event throughput, failures, enabling proactive

issue detection, reducing downtime, and improving reliability and platform performance for millions of global users simultaneously.

• Collaborated with DevOps teams on global SaaS deployments using AWS CloudFormation, Helm charts, blue-green strategies, and deployment