• Contributed to building scalable merchant-facing applications using React, TypeScript, and Node.js in a multi-tenant environment

• Designed and optimized REST APIs handling 150K requests/day, improving reliability through better error handling, validation, and rate limiting

• Reduced API latency by 25% by optimizing PostgreSQL queries, adding indexing, and improving data access patterns

• Developed serverless and event-driven workflows using AWS Lambda, API Gateway, and SQS to handle asynchronous processing

• Integrated AI-powered features using LLM APIs to enhance merchant recommendations and automate routine support workflows

• Improved observability by implementing structured logging and monitoring with CloudWatch, reducing debugging time

• Collaborated with cross-functional teams to deliver production features impacting merchant workflows and internal tools

• Increased test coverage to 80% using Jest and integration testing, improving system stability and release confidence

• Developed and maintained full-stack features for Cority's EHS (Environmental, Health & Safety) SaaS platform using React, TypeScript, and Node.js

• Built and enhanced RESTful APIs for core platform modules including incident management, audit tracking, and compliance reporting, handling high-volume enterprise data reliably

• Optimized PostgreSQL queries and introduced strategic indexing across critical reporting workflows, reducing average query execution time by 35%

• Designed and implemented event-driven microservices using AWS SQS and Lambda to automate compliance notifications and background data processing tasks

• Integrated AI-powered features using LLM APIs to assist users with intelligent form suggestions and automated risk classification, reducing manual data entry effort by 25%

• Improved frontend performance and accessibility of complex data-heavy dashboards using React and D3.js, resulting in measurably faster load times for enterprise users

• Strengthened platform security by implementing JWT-based authentication, RBAC, and audit logging across sensitive EHS data workflows

• Contributed to CI/CD pipeline improvements using GitHub Actions and Docker, increasing deployment frequency and reducing release cycle time by 20%

• Built internal tools and dashboards using React, Node.js, and Python, enabling efficient data access for 50K users

• Developed reusable microservices and REST/GraphQL APIs, improving modularity and reducing development time by 25%

• Integrated ML model APIs and AI-driven analytics pipelines into production systems, enabling real-time decision automation and intelligent financial insights

• Leveraged prompt engineering and LLM APIs to prototype an AI assistant for internal tooling, reducing analyst query time by 35%

• Improved system reliability (97% uptime) through enhanced monitoring, alerting, and fault-tolerant design patterns

• Reduced MTTR by 40% by debugging production issues using logs, metrics, and distributed tracing approaches

• Participated in code reviews, CI/CD pipelines, and test automation practices

• Developed scalable web applications using Angular and Node.js, supporting 10K+ concurrent users

• Built RESTful APIs and backend services with Express.js, improving performance and maintainability

• Designed real-time features using WebSockets for notifications and live updates

• Optimized database performance (PostgreSQL, MongoDB) using indexing, query tuning, and schema design achieving 60% improvement in query speed

• Implemented authentication and authorization using JWT and RBAC

• Containerized applications using Docker and improved CI/CD pipelines, reducing deployment time by 60%

• Explored early AI/ML integrations for predictive analytics use cases, working with data science teams to serve model outputs through backend APIs

• Worked closely with QA and DevOps teams to ensure production stability and smooth releases