You will get a Secure & Scalable Node.js Backend
Project details
Need a powerful backend to support your product? I’ll build a Node. J.S-based backend that’s secure, scalable, and API-ready using Nest.js, Express, PostgreSQL, and Redis.
Each backend comes with clean code, test coverage, environment configuration, and deployment-ready support.
Secure RESTful APIs or GraphQL
PostgreSQL DB schema + indexes
Redis caching for speed and reliability
Authentication: JWT, OAuth, or session
Background jobs and error logging
Swagger or Postman API documentation
Perfect for SaaS platforms, admin portals, eCommerce, or internal tools.
Each backend comes with clean code, test coverage, environment configuration, and deployment-ready support.
Secure RESTful APIs or GraphQL
PostgreSQL DB schema + indexes
Redis caching for speed and reliability
Authentication: JWT, OAuth, or session
Background jobs and error logging
Swagger or Postman API documentation
Perfect for SaaS platforms, admin portals, eCommerce, or internal tools.
Programming Languages
HTML & CSS, JavaScript, PythonCoding Expertise
Cross Browser & Device Compatibility, Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$2,500
|
Standard
$4,800
|
Advanced
$6,000
|
|---|---|---|---|
| Delivery Time | 8 days | 15 days | 20 days |
Number of Revisions | 1 | 2 | Unlimited |
Number of Pages | 10 | 20 | 30 |
Design Customization | |||
Content Upload | |||
Responsive Design | - | ||
Source Code | - | - |
About Adnan
Senior Backend Engineer | Ruby, NestJS, RAG Architectures
Khushab, Pakistan - 6:53 am local time
Core Backend Development:
- Design RESTful and GraphQL APIs with NestJS and Node.js frameworks
- Build scalable Ruby on Rails applications with optimized database queries
- Implement microservices architecture using Docker and Kubernetes
- Configure PostgreSQL, MongoDB, and Redis for optimal performance
- Set up CI/CD pipelines and automated testing frameworks
RAG and AI Integration Expertise:
- Develop RAG (Retrieval-Augmented Generation) pipelines using LangChain and LlamaIndex
- Build intelligent document processing systems with vector databases (Pinecone, Weaviate)
- Create custom AI agents with contextual search capabilities
- Integrate OpenAI, Claude, and open-source LLMs into backend services
- Implement semantic search and knowledge retrieval systems
Technical Proficiencies:
- Backend: Ruby on Rails, NestJS, Node.js, Express.js, FastAPI
- Databases: PostgreSQL, MongoDB, Redis, Elasticsearch, Vector DBs
- AI/ML: LangChain, LlamaIndex, RAG architectures, embedding models
- Infrastructure: AWS, Docker, Kubernetes, serverless architectures
- Testing: Jest, RSpec, integration testing, load testing
Recent Project Highlights:
- Architected RAG system processing 100,000+ documents with 95% accuracy
- Migrated legacy Ruby monolith to microservices, reducing response time by 60%
- Built NestJS API handling 50M+ monthly requests with 99.9% uptime
- Developed AI-powered document analysis pipeline reducing manual processing by 80%
I deliver clean, documented, test-covered code that your team can maintain and extend. Every system includes comprehensive documentation, deployment guides, and knowledge transfer.
Available for long-term contracts and ongoing collaboration. Response time within 2 hours during business hours.
Steps for completing your project
After purchasing the project, send requirements so Adnan can start the project.
Delivery time starts when Adnan receives requirements from you.
Adnan works on your project following the steps below.
Revisions may occur after the delivery date.
Let's connect and discuss your project requirements in detail.
I will provide you with a detailed breakdown of the project over chat.