Krishna Yadav

About Krishna Yadav

Full-stack Developer and Engineering Manager with 12 years of experience architecting and delivering scalable, responsive, and user-centric web applications.Extensive background in developing cross-platform single-page applications using MEAN/MERN stacks and modern front-end frameworks such as Angular and React.Proficient in building mobile-first, accessible interfaces using JavaScript, TypeScript, HTML5, CSS3, SASS, and CSS Grid.Skilled in leading cross-functional teams, defining coding standards, and driving CI/CD practices across cloud-native deployments on Azure, GCP and AWS.

Experience

1. Engineering Manager

   EY

   Jun 2018 — Present

   As Engineering Manager and UI Lead at Ernst & Young (EY) since June 2018, Krishna Yadav has spearheaded the modernization of multiple client-facing web applications, transforming legacy desktop interfaces into responsive, mobile-first experiences using Angular, React, and TypeScript. Krishna led cross-functional teams of frontend and backend engineers to deliver enterprise-grade applications built on MEAN and MERN stacks, aligning technical execution with strategic business goals. Krishna architected and deployed over a dozen RESTful microservices using Node.js and Express.js, containerized with Docker and orchestrated via Azure Kubernetes Service (AKS), ensuring scalability, performance, and secure API integration. Krishna authored YAML-based CI/CD pipelines and Kubernetes deployment configurations to streamline release workflows and maintain production readiness. Krishna also built a global search engine enabling federated queries across MongoDB instances, and integrated advanced data visualization tools such as Power BI, D3.js, and Kendo UI. Krishna collaborated closely with product owners, UX designers, and DevOps teams to translate business requirements into actionable engineering tasks, while mentoring developers and establishing coding standards. Krishna championed accessibility (WCAG), observability (Splunk, Dynatrace), and performance optimization through lazy loading, code splitting, and Webpack tuning. Krishna also contributed to agentic AI development using GPT-4 and LangGraph, integrating Retrieval-Augmented Generation (RAG) pipelines into Python-based web applications deployed via Azure AI Foundry.