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Experience

Fullstack Engineer · Remote

Weya.ai | AI Workflow Automation for BFSIApr 2025 - Aug 2025
  • Engineered a multi-prompt calling agent builder using a node-based visual editor, enabling conditional conversational flows with branching logic (call pickup, hang-up paths), multilingual support, and real-time state synchronization.
  • Designed and implemented a visual workflow orchestration system using React Flow, enabling users to design, edit, and manage multi-agent workflows (Phone, WhatsApp, Email) via drag-and-drop UI, third-party tool integration and cross-agent coordination.
  • Built real-time analytics dashboards with D3.js visualizing call volume, success rates, and latency through interactive filtering and time-series aggregation for live agent performance monitoring.
  • Optimized Next.js performance using React Query caching, route-based code splitting, React.lazy() with Suspense, and ISR, reducing Time to Interactive (TTI) by 40%.
  • Architected multi-factor authentication with OAuth 2.0 (@react-oauth/google), TOTP verification, JWT access/refresh token rotation with HttpOnly cookies, and role-based access control (RBAC) middleware.
  • Resolved Next.js crashes caused by client-side pagination when processing 100k+ agent call records by implementing server-side pagination using MongoDB aggregation pipelines, reducing client-side memory footprint by 75%.
  • Automated voice pipeline using Python and ElevenLabs API for TTS generation across multilingual agents, integrated AWS S3 with SSE-S3 encryption, and developed Node.js API with AWS SDK for pre-signed URL generation.
  • Played a key role in developing distributed microservices in Go, using Azure Queue Service for message brokering and Redis for state management, implementing a weighted round-robin scheduling algorithm for real-time multi-agent calls.

Next.js Developer · Upwork

HeyMilo AIDec 24 - Jan 25
  • Integrated Daily.co and Vapi SDK for video conferencing features, enhancing the platform’s video interview capabilities.
  • Leveraged Vapi’s iframe object to create a seamless connection to Daily.co rooms, ensuring synchronization between the AI assistant and video conferencing.
  • Utilized TypeScript for type safety and enhanced code maintainability, ensuring fewer runtime errors.
  • Designed and implemented responsive and accessible user interfaces using Next.js, ensuring a consistent experience across devices.
  • Optimized existing components for better performance and maintainability, reducing loading times by 25%.

Machine Learning Trainee

ThinkNEXT Technologies Private LimitedJuly 22 - Aug 22
  • Employed advanced Machine Learning algorithms to predict automobile prices based on crucial factors.
  • Trained a Linear Regression model and leveraged feature engineering techniques and popular libraries like NumPy, Pandas, and Matplotlib, achieving a nuanced understanding of how different vehicle attributes impact their market price.
  • Planned future enhancements to refine the model and explore additional features for real-world deployment.