 Developed the customer-facing web app from scratch using React + Material UI with a Node.js (Express) backend, supporting end-to-end kitchen discovery and booking flows used by live food sellers.

 Designed backend APIs in Node.js and Python with DynamoDB, handling kitchen availability, pricing

rules, and booking state while keeping response times under 300 ms for core flows.

 Set up automated build and deployment using GitHub Actions + AWS, cutting manual release effort and reducing average deployment time from 30 minutes to under 10 minutes.

 Implemented an AI-based kitchen matching flow using Python + LLM APIs, ranking kitchens by location, availability, and seller requirements, which reduced manual kitchen shortlisting by 40%.

 Architected an early RAG prototype using Python, embeddings, and vector search to answer seller queries about kitchen rules and onboarding steps, lowering support follow-ups during onboarding by 25%.

 Designed Python-based backend services to ingest and normalize large-scale tax and financial documents, processing millions of records each filing season with validation rules aligned to compliance workflows.

 Implemented LLM-driven classification and data extraction pipelines in Python, orchestrated through AWS Lambda and SQS, reducing manual review effort for tax operations teams by 32% during peak periods.

 Developed an internal RAG service using Python, embeddings, and vector search on AWS-managed

storage, enabling fast retrieval of tax policy guidance, cutting analyst lookup time from minutes to seconds.

 Integrated AI services with core Intuit platforms using REST APIs deployed on AWS (API Gateway,

ECS), enforcing IAM-based access controls, audit logging, and stable latency under seasonal traffic spikes.

 Added production monitoring and safety fallbacks using CloudWatch metrics and Python-based

confidence checks, lowering incorrect AI-assisted suggestions by 18% during high-volume filings.

 Delivered modular enterprise applications using Python (Django), React with TypeScript, and

PostgreSQL, supporting 100K+ monthly transactions while maintaining 99.95% uptime for client-facing

workflows.

 Reworked release and environment workflows through Git-based CI/CD and AWS, cutting average

deployment time from 45 minutes to 7 minutes and reducing rollback incidents during peak releases.

 Developed REST and GraphQL APIs using Django REST Framework and Node.js (Express) to replace

manual business operations, saving an estimated 5,000+ client labor hours annually.

 Implemented a real-time logistics and shipment tracking system using Python, Flask, WebSockets, and

PostgreSQL, enabling live visibility across 15+ countries and lowering delivery delays by 42%.

 Delivered executive reporting dashboards using React and Recharts backed by Django APIs, consolidating fragmented data sources and improving reporting accuracy from 68% to 99.6%.

 Developed complex user-facing dashboards using React, JavaScript, and REST APIs, handling multi-step forms, role-based views, and client-side state that reduced user task completion time by 35%.

 Implemented backend services in Node.js with Express to manage authentication, permissions, and

transactional workflows, supporting concurrent usage from 1,000+ active users without session conflicts.

 Designed relational data models and query logic in PostgreSQL, optimizing joins and indexes that cut slow API response cases by 40% in production environments.

 Integrated third-party services such as payment gateways, email notifications, and file uploads using Node.js, reducing manual operational steps for internal teams by over 50%.

 Collaborated closely with product and QA teams to translate evolving requirements into shippable features, shipping weekly releases through Git-based workflows with fewer post-release fixes over time.