Full Stack Software Developer
Full-Stack Engineer
Available for hire
Years of
experience
2+ years
Experience
level
Mid-level
Available
for
Full-time, Part-time, Contract, Freelance
Available from
27 Apr 2026
Hi, This is Raju Mannem, With 2 year’s hands on experience in shipping Full Stack Software applications from prototyping, designing, developing and maintaining cloud native applications in production environments. Currently working for a US based startup, contributed to scalable systems, LLM driven automation, and performance critical features. I have been recognized for improving operational efficiency, resolving complex issues, and real time problems. I'm open to discuss any opportunities, comfortable to collaborate and work across all time zone and ready to make long term contributions to the team.
A short intro about me • Designing software applications for business needs. • Workflow orchestration, performance optimization and model deployment. • Helped 2 customers to manage and grow their business. Portfolio: https://ctgpx2w64f.ap-south-1.awsapprunner.com/ Linkedin: https://raju-mannem.appwrite.network/
Skills
JavaScript
CSS
TypeScript
React.js
Next.js
Node.js
Express.js
Tailwind CSS
SQL
Redis
GraphQL
Docker
AWS
Vercel
Framer Motion
Redux.js
Zod
Software as a Service
NoSQL
REST
Lambda
JIRA
Terraform
Supabase
OpenAI
jQuery
D3.js
JSON
Apollo
Mongoose
Netlify
React Query
JWT
JSX
NextAuth
Material UI
PostCSS
Responsive design
MERN stack
MongoDB
PostgreSQL
MySQL
Firebase
Firestore
TypeORM
Cloudflare
Git
GitHub
Figma
Prisma
CI/CD
Web services
Machine Learning
Web security
Stripe
PayPal
Payment gateways
Serverless
OAuth
E-commerce
Single Page Application
Server Side Rendering
Server Side Generation
Platform as a Service
Generative AI
HTML
Python
Bash
Shell
PowerShell
Flask
NumPy
Pandas
Cloudwatch
Hugging Face
LangChain
Languages
Employment History
full stack developer at
freelance
2025
-
2026
Project - Campuslogics CMS – LMS
Client Challenge:
Lack of functionality for conducting tests, notifying updates to end users, course creation, payment system and secure DRM system for course access
System Architecture and Responsibilities:
Designed normalized PostgreSQL schema with Prisma.
Built GraphQL APIs with Apollo Server and optimized caching.
Implemented secure authentication (JWT, OAuth, NextAuth, SSO integrations).
Rebuilt frontend using Next.js (SSR + ISR) with TypeScript.
Integrated file storage (S3 + CloudFront + ImageKit).
Built CI/CD with GCP Cloud Build + GitHub Actions.
Deployed on AWS Lambda, App Runner, and GCP Cloud Run.
Participated in on-call production incident handling.
Metrics:
Improved page load performance by 45%.
Reduced database query time by 35%.
Increased Lighthouse SEO score from 62 - 92.
Improved user engagement by 39%.
Improved SEO indexing and discoverability via structured metadata and Open Graph optimization.
Improved production stability via CI/CD automation and testing.
Optimized GraphQL resolvers to reduce over fetching.
Used ISR & caching to reduce server compute load.
full stack developer at
zeus systems inc
2024
-
2026
Project: AI Document Parsing and Knowledge Automation Platform
Client Challenge:
Manual document comparison and bio data extraction from scanned images and PDFs resulted in inconsistent validation and heavy human intervention, inconsistent data, and required human intervention for validation and data accessibility
System Architecture and Responsibilities:
Designed RAG LLM system with structured context injection.
Built Node.js + Express inference APIs and optimized MongoDB schemas.
Secured APIs using JWE, Zod validation, and role based access control.
Developed Next.js frontend (TypeScript, Tailwind) for parsing and data workflows.
Implemented Jest + RTL testing integrated into CI/CD.
Provisioned AWS infrastructure using Terraform (S3, CloudFront, Lambda, App Runner).
Containerized services with Docker and deployed via GitHub Actions.
Implemented observability stack (CloudWatch, Prometheus, Grafana).
Metrics:
Reduced API latency from 1.8s - 750ms (58% improvement).
Reduced manual document processing time by 90-95%.
Improved structured data extraction efficiency by 35%.
Maintained 99.9% production uptime.
Reduced post deployment bugs by 30% via automated testing.
Implemented centralized monitoring and alerting to reduce incident response time.
Optimized serverless architecture reducing unnecessary compute invocations.
Improved retrieval precision, reducing redundant LLM token usage.
Improved LLM answer relevance by 40% via retrieval optimization.
Reduced hallucination rate through context-constrained prompting and embedding filtering.
Increased response validation consistency by 35–45%.
Education
Master of Computer Applications at
JKC College
2023
-
2025
Bachelor of Computer Science at
JKC College
2020
-
2023