Summary
Driving web performance, design systems, and AI-driven frontend innovation.
I build scalable frontend systems with extensive experience in Next.js, React, and Web Performance Optimization (Core Web Vitals). Currently exploring the intersection of Frontend Engineering and Generative AI to enhance developer productivity and user experiences.
Location: Delhi, India
Experience
Tech Lead
Leading the frontend team for Recruiter and Jobseeker products. Architected a centralized Design System using Storybook and Lerna. Improved Core Web Vitals to 'Good' range, optimizing LCP and CLS. Driving AI initiatives for developer productivity (30% efficiency boost) and building Agentic AI POCs.
Lead Engineer
Focused on web performance monitoring and optimization. Implemented event batching with IndexedDB reducing network calls by 40%.
Senior Software Engineer
Led frontend development for public insurance website (health, travel, motor). Delivered scalable policy purchase flows and optimized large-scale traffic handling.
Software Engineer
Developed ad-tech and educational web applications focusing on performance and UX.
Software Engineer
Developed enterprise applications and integrated frontend modules with backend APIs.
Featured Projects
Centralized Design System
A scalable design system with CSS tokens, Tailwind integration, and component library architecture.
Architected and scaled a centralized design system to standardize UI components across multiple products. Implemented a token-based theming system using CSS variables mapped to Tailwind utilities, created a comprehensive typography scale, and built reusable component packages. The system uses Storybook for documentation and Lerna for monorepo management, accelerating product development cycles and ensuring UI consistency.
Web Vitals Monitoring Dashboard
Comprehensive Web Vitals tracking system with attribution data, backend logging, and analytics dashboards.
Built a production-ready Web Vitals monitoring system using the web-vitals library with attribution support. Implemented tracking for all Core Web Vitals (LCP, CLS, INP, FCP, TTFB) with detailed attribution data, intelligent SPA navigation handling, and backend logging. Collaborated with the data analysis team to create visualizations and alerting systems that enabled data-driven performance optimizations.
LLM Chatbot with Multi-Agent System
Intelligent chatbot using Mastra Framework, AI SDK, and OpenAI with multi-agent routing and tool-based agent calls.
Built a production-ready LLM chatbot using Mastra Framework and AI SDK. Implemented a root agent and sub-agent architecture where the root agent (Recruiting Agent) handles simple conversations directly and routes complex queries to a specialized sub-agent (Recruiter Query Handler Agent) via tools. Features conversation continuity through MongoDB memory, streaming responses, and human-in-the-loop interactions for enhanced user experience.
Agentic AI Telephony Solution
Production telephony solution using Deepgram, ElevenLabs, OpenAI GPT Realtime, and Plivo with intelligent interruption detection.
Built a production-ready telephony solution integrating Deepgram for real-time speech-to-text, ElevenLabs for natural text-to-speech, OpenAI GPT Realtime API for conversational AI, and Plivo for telephony infrastructure. Implemented intelligent interruption detection that filters acknowledgment words and uses intent severity levels to enable natural conversation flow with minimal latency.
AI-Driven Developer Efficiency
Leveraged Cursor Rules and MCP integrations with Jira and Figma to automate design-to-code workflows, task management, and PRD gap analysis.
Developed an AI-driven workflow system using Cursor Rules and MCP (Model Context Protocol) integrations to significantly improve developer efficiency. Collaborated with designers to establish design token guidelines in Figma, which were then codified into Cursor Rules for automated Figma-to-code conversion achieving 80% design match accuracy. Integrated Jira MCP for automated task and subtask creation, and Figma MCP for design component generation. Created comprehensive tech documentation for features to enable LLM understanding of business use cases, and implemented PRD parsing via code to identify gaps proactively before development begins.
Technical Skills
References available upon request.