You will get High-Performance Real-Time Backends & APIs Built with Node.js
Project details
As a Backend Engineer on Tezdealz, I developed a scalable, high-performance backend for a car sales and purchase platform. Built with Node.js, Express.js, and MongoDB, the system included real-time communication via Socket.io and asynchronous processing through RabbitMQ. I also implemented smart data scraping to auto-populate listings from external sources. The architecture ensured seamless interactions between users and enabled a fluid, responsive user experience.
Key Responsibilities & Contributions:
• Designed and implemented microservices using Node.js and Express.js
• Integrated real-time updates with Socket.io and message queues via RabbitMQ
• Developed scraping tools for dynamic content aggregation
• Structured scalable data models using MongoDB
• Collaborated closely with the React Native team to support cross-platform access
Project Highlights:
• Built a real-time, event-driven system from scratch
• Optimized backend performance for scalability and responsiveness
• Experience integrating data pipelines and asynchronous workflows
• Delivered a backend architecture ready for production at scale
Key Responsibilities & Contributions:
• Designed and implemented microservices using Node.js and Express.js
• Integrated real-time updates with Socket.io and message queues via RabbitMQ
• Developed scraping tools for dynamic content aggregation
• Structured scalable data models using MongoDB
• Collaborated closely with the React Native team to support cross-platform access
Project Highlights:
• Built a real-time, event-driven system from scratch
• Optimized backend performance for scalability and responsiveness
• Experience integrating data pipelines and asynchronous workflows
• Delivered a backend architecture ready for production at scale
Programming Languages
HTML & CSS, JavaScript, TypeScriptCoding Expertise
Performance Optimization, Security, DesignWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$700
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 12 days |
Number of Revisions | 2 | 2 | 2 |
Number of Pages | 3 | 5 | 10 |
Design Customization | - | - | - |
Content Upload | |||
Responsive Design | - | - | - |
Source Code |
2 reviews
(2)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
AH
Alex H.
Jun 2, 2025
Developer Wanted To Join Our Back-End Team
AL
Austin L.
May 8, 2025
Need Senior Full-Stack Developer to Fix a Feature and Optimize Backend (Next.js + PostgreSQL)
Azeem did an exceptional job — he not only fixed the unreliable save/load functionality in my app, but also quickly identified and resolved performance issues I didn’t even know existed. His debugging skills are top-tier, he worked fast, communicated clearly throughout, and delivered clean, well-documented code. Highly recommended if you need a full-stack expert who genuinely cares about quality, speed, and performance.
About Azeem
Full-Stack AI Engineer | LangChain | RAG | Elixir | Node.js | PenTest
100%
Job Success
Lahore, Pakistan - 8:14 pm local time
I'm a senior LLM engineer, TypeScript AI developer, LangChain developer, and RAG pipeline developer, building production AI systems with OpenAI, Anthropic Claude, and vector databases.
6 years. 40+ systems shipped.
TypeScript and NodeJS on the product layer, LangChain and AI agents on the intelligence layer, full stack across both.
Fewer than 200 Upwork profiles list Elixir/Phoenix; I have shipped it under real load. I also test web applications against the OWASP Top 10. I design the AI layer, scale the backend, and find security gaps before they find you.
AI and LLM: LangChain, LangChain JS, LangGraph, RAG pipelines, OpenAI, Anthropic Claude, Google Gemini, Vercel AI SDK, pgvector, Pinecone, prompt engineering, multi-agent systems, AI workflow automation
Infrastructure and Backend: TypeScript, NodeJS, NextJS, Python, Elixir/Phoenix, Ethereum, PostgreSQL, MongoDB, Redis, BullMQ, Pusher, Docker, Kubernetes, AWS, WebSockets, Playwright,
OWASP
BY THE NUMBERS
40% faster response times through query optimization and Redis caching
50% faster deployments through containerization and CI/CD
14 Playwright E2E test suites before a single feature went live
WHAT I'VE SHIPPED
Legal teams uploading contracts got answers that were confidently wrong because retrieval splits liability clauses across fixed token windows. At 512 tokens a clause becomes orphaned fragments and the model answers from the fragments. In legal work that is a liability. I built a LangChain RAG pipeline chunking at clause boundaries with source citation enforced at the retrieval layer. Without it a legal AI assistant is just a hallucination engine with a clean UI.
Enterprise law firm AI: Agent Router to Diary, Drafting, and Billing agents, each getting only the context its task requires. Sovereign RAG in Australian infrastructure, namespaces isolated per firm. LangGraph, Google Gemini, pgvector.
Autonomous agent platform: Budget gates fire before each tool call. Agents self-terminate at spending limits, every action logged. OpenAI, Anthropic Claude, TypeScript.
Multi-source quiz SaaS: LangChain pipeline normalizing PDF, DOCX, YouTube, and web through one text-splitter. Structured generation enforces Q&A schema, not freeform output. LangChain, OpenAI, NextJS.
Multi-source document chat: Five source types through one ingestion pipeline, Vercel AI SDK streaming, Stripe billing. NextJS, Vercel AI SDK, OpenAI, pgvector.
NFT horse racing platform: Phoenix Channels for thousands of concurrent viewers on real-money races. Ethereum event listeners kept wallet state in sync. A missed on-chain event is a missed payout. React, Elixir/Phoenix, Ethereum.
Real-time classroom SaaS: SocketIO as a containerized microservice, Redis pub/sub for horizontal scaling, WebRTC for peer video, 14 Playwright suites before go-live. SocketIO, Redis, WebRTC, Docker.
Math tutoring platform: KaTeX rendering identically on both ends over Pusher WebSockets. Session replay engine and PDF export give tutors a verifiable audit trail. Pusher, KaTeX, NextJS.
Web scraping API: BullMQ worker microservice, concurrency of 3, retry logic, outbound webhooks on completion. API-key auth and Stripe billing. BullMQ, Redis, NodeJS.
OWASP security testing: Penetration testing against the OWASP Top 10, authorization gap analysis, findings reports before enterprise sales or funding rounds.
Car marketplace platform: Multi-step listing flow, dynamic search, buyer and seller portals, image pipeline. NextJS, PostgreSQL, AWS S3.
Fintech investment platform: Real-time portfolio tracking, transaction ledger, role-based access, Stripe billing. NextJS, MongoDB, TypeScript.
Construction company SaaS: Project scheduling, contractor management, client portal, document management. NextJS, PostgreSQL, AWS S3.
SaaS billing dashboard: Multi-tier subscriptions, usage-based billing, revenue analytics, Stripe webhooks. NextJS, Stripe, PostgreSQL.
Project management SaaS: Kanban boards, task assignment, time tracking, team collaboration, real-time updates. NextJS, PostgreSQL, TypeScript.
WHO I WORK WITH
Every engagement starts with a fixed-price discovery milestone scoped before a single line of code is written. I work with founders who need someone to own the full build and technical leads who need someone to own the architecture. Both get the same: a defined done condition, documented architecture, test coverage, and a recorded walkthrough the next engineer can follow on day one.
Clients tell me the handoff is as useful as the build and that the scoping conversation saved them from building the wrong thing.
Send me a message even a rough one. First conversation is free: 30 minutes, no commitment, and you will leave knowing whether what you need is buildable.
Steps for completing your project
After purchasing the project, send requirements so Azeem can start the project.
Delivery time starts when Azeem receives requirements from you.
Azeem works on your project following the steps below.
Revisions may occur after the delivery date.
Project Development
I begin working on the project according to the agreed plan and timeline. Regular updates are provided through the workroom to keep you informed of the progress.
Client Reviews & Provides Feedback
Once the project is complete, the client reviews the work and provides any necessary revisions or approvals.