Rishita – Typescript, React, .NET

Rishita contributed to the modernization of a large-scale investment platform by transitioning monolithic systems into distributed .NET Core microservices hosted on Azure. Beyond the core architecture work, she helped integrate AI-driven insights into the system using Azure OpenAI LLM APIs. These capabilities allowed the platform to surface contextual recommendations, anomaly alerts, and portfolio summaries directly within the React front-end. Her role encompassed backend API design, Kafka event streaming, and the development of secure data pipelines for real-time analytics and AI enrichment.

• Delivered a modular .NET microservice architecture that reduced system coupling and improved release cadence.
• Integrated Azure OpenAI LLMs into existing APIs to generate portfolio summaries and predictive insights, improving analyst efficiency by 25%.
• Designed and implemented .NET Core APIs with Kafka-based communication for real-time portfolio updates and built React micro-frontends secured with Azure AD.
• Implemented CI/CD pipelines in Azure DevOps, reducing deployment time from 2 hours to 15 minutes.
• Enabled real-time event updates via Kafka, enhancing the accuracy of investment dashboards.
• Optimized SQL queries and indexing, increasing data retrieval speed by 40%.

A real-time trading dashboard for the company’s trading and risk teams. The solution ingested high-frequency financial data streams via Kafka and exposed them through ASP.NET APIs, which were consumed by React and Vue frontends. The dashboards provided live updates on trade executions and compliance metrics, allowing teams to make instant, data-driven decisions.

• Built APIs capable of handling over 5 million trade events per day with sub-second response times.
• Representing the team with Stakeholder and user demos.
• Integrated ElasticSearch for audit querying, cutting report generation time from 5 minutes to under 10 seconds.
• Reduced frontend latency by 40% through WebSocket optimization and efficient state management.
• Delivered stable CI/CD pipelines with GitHub Actions and AWS CodePipeline for automated builds and testing.

A cloud-based analytics pipeline for healthcare data, where clinical metrics were processed and visualized for medical researchers. The system combined Azure Functions for serverless event processing, Kafka for asynchronous messaging, and Vue.js for front-end dashboards. The architecture supported scalable ingestion and real-time visualization of high-volume medical datasets.

• Reduced data processing latency by 40% using asynchronous Kafka event flows.
• Automated infrastructure provisioning via Terraform, minimizing manual deployment errors.
• Delivered browser-compatible Vue.js dashboards for clinicians to visualize live patient data.
• Ensured HIPAA-compliant handling of patient information with secure authentication and encryption layers.

A device management web application for monitoring IoT devices across the company’s hardware ecosystem. The system consumed telemetry data from MQTT brokers and visualized it using React and D3.js. Rishita's work focused on building a fast, responsive UI and optimizing API layers for high-frequency sensor streams.

• Designed data visualizations that supported real-time telemetry for 10,000+ connected devices.
• Optimized backend queries, improving API response times by 25%.
• Introduced Docker-based environments, cutting development setup time by 70%.
• Strengthened system stability with caching strategies and fault-tolerant MQTT message handling.