Bhuvaneswar Reddy Marreddy

Project: Election Management Platform

• •Drove API consistency across services — standardized request/response contracts, validation patterns, and versioning strategy adopted team-wide
• •Built a reusable Blazor/Razor Pages component library — reduced UI duplication across screens and established consistent state management patterns
• •Owned containerized service deployments to Azure App Service and Container Apps — managed env configs, rollout strategies, and release gates through Azure DevOps
• •Built and maintained YAML CI/CD pipelines — eliminated manual release steps and enabled reliable, repeatable deploys across dev, staging, and production
• •Centralized cross-cutting concerns in the ASP.NET Core pipeline — exception handling, request tracing, and auth enforcement applied consistently across all services rather than scattered per-endpoint
• •Established observability standards with Application Insights — structured logging, dependency tracking, and health checks that became the baseline for diagnosing production issues
• •Tuned Azure AI Search to deliver sub-second response times across 13M+ records — custom index design, filtering strategies, and wildcard handling for complex real-world query scenarios
• •Designed Azure Data Factory pipelines with validation checkpoints and rollback handling — ensuring controlled, repeatable data loads across environments
• •Decoupled long-running workflows from the request pipeline using Azure Service Bus and .NET Worker Services — improved system responsiveness and made background processing independently scalable
• •Modeled Cosmos DB and MongoDB schemas around access patterns rather than entity relationships — avoided cross-partition queries and kept reads predictable under load
• •Introduced shared .NET class libraries for DTOs and the repository layer — single source of truth across UI, API, and worker services, eliminating duplicated contracts and drift between teams
• •Trusted for production escalations — trace issues end-to-end across UI, API, and data layers; known for fixes that hold under load without introducing regressions
• •Set the bar in code reviews — feedback focused on architecture consistency, maintainability, and catching issues that slip past functional testing
• •Implemented and hardened auth flows end-to-end — Azure AD/Entra ID SSO, OAuth2/OIDC, and JWT; validated security boundaries using Swagger and Postman before every release

Project: ProcureGPT (AI Chatbot / Procurement Assistant Prototype)

• •Designed the backend architecture for an LLM-powered chatbot — prompt routing, tool/function dispatch, and response contracts shaped to keep the React UI fast and stateless
• •Applied RAG and LangChain patterns to ground responses in procurement knowledge sources — measurably reduced hallucinations during stakeholder evaluations
• •Architected multi-tenancy with secure session isolation, route guards, and RBAC from the start — avoiding the retrofitting cost that derails most early-stage AI prototypes
• •Shipped the full stack on GCP — containerized services, environment-specific config, integration testing, and release readiness for stakeholder demos
• •Built reusable React components with hooks/context patterns — performance-focused, consistent SCSS styling, and predictable re-render behavior
• •Ran structured evaluation cycles on prompt templates and retrieval pipelines — each iteration measured against procurement-specific test cases rather than intuition
• •Simplified complex integration flows and wrote runbooks that cut new engineer onboarding time significantly

Project: InfyMe (Internal Employee Services Portal)

• •Built Angular/TypeScript UI features tightly integrated with backend APIs — focused on usability consistency across a large, shared component surface
• •Designed RESTful APIs with structured JSON contracts — validation and error handling built to a standard that held across multiple consuming teams
• •Managed SQL Server schema changes with backward compatibility in mind — no breaking changes to dependent services across releases
• •Collaborated with QA and product teams end-to-end — from sprint planning through UAT sign-off and production release
• •Owned defect resolution for production issues — log analysis, root cause identification, and regression-safe patches shipped under sprint timelines
• •Active in code reviews with feedback that raised API contract consistency and reduced review cycles over time
• •Implemented JWT-based authorization patterns and validated API contracts using Swagger/OpenAPI and Postman
• •Contributed to CI/CD workflows in Azure DevOps — stable build pipelines and clean handoffs to QA and support teams