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English
$
USD
I will engineer enterprise ai agents, rag pipelines, and smart chatbots
Hasnain R
About this gig
Most AI apps are fragile wrapper scripts. I build secure, production-ready AI infrastructure.
As a Full-Stack AI Engineer & Systems Architect, I specialize in integrating LLMs into enterprise workflows. I work strictly "document-first"designing vector DB schemas, API routing, and agentic workflows before coding begins.
What I Build:
- RAG Systems: Context-aware AI using Vector DBs to securely query your proprietary PDFs and databases.
- Agentic Workflows: Autonomous agents (n8n/LangGraph) that execute multi-step tasks across APIs, CRMs, and ERPs.
- Custom AI Copilots: Interfaces built on React/Next.js with highly secure Python/FastAPI or Node.js backends.
- Predictive ML & Tuning: Integrating foundation models and predictive logic (XGBoost) into decision-support systems.
Tech Stack: OpenAI, Claude, Llama, LangChain, LlamaIndex, Python, Node.js, React, Next.js, Docker, n8n, Supabase.
I don't hack together quick templates. I build compliant, scalable AI architecture.
Message me with your requirements to map out your system before we build!
Get to know Hasnain R
Hasnain R
Full Stack MERN Developer Data Science AI Integration Architect
- FromPakistan
- Member sinceSep 2024
- Avg. response time1 hour
Languages
English
With 3.5+ years of industry experience, I am a certified Full-Stack MERN Engineer and Data Scientist. I bridge modern web architecture with advanced AI, building intelligent, scalable apps for FinTech (like LMS) and EdTech and more.
My Core Expertise:
Full-Stack & Mobile: MERN, Next.js, Vue, React Native, MySQL.
AI Integrations: Embedding custom NLP & smart algorithms.
Architecture: Secure, high-performance enterprise dashboards.
I am a problem solver ready to adapt to your business goals. Let's engineer the right solution together!
My Portfolio
FAQ
What do you mean by a "document-first" approach?
Before writing any code, I map out your system architecture, vector DB schemas, and API routes in a formal document. This locks down security and business logic upfront, preventing costly rewrites and ensuring the system scales perfectly.
Will my proprietary business data be secure?
Yes. I build enterprise-grade systems. We use private vector databases and secure API endpoints. If strict compliance is needed, we can deploy via Azure OpenAI or use secure local models (Ollama/Llama) so data never leaves your servers.
What is an "Agentic Workflow" and how is it different from a chatbot?
A standard chatbot just answers questions. An agentic workflow uses frameworks like LangGraph or n8n to let the AI take action—such as querying your SQL database, analyzing the data, and automatically updating your CRM or sending emails.
Do I need RAG or model fine-tuning for my project?
RAG is best for giving the AI access to your private knowledge base (PDFs, internal docs). Fine-tuning is used to change the AI's core behavior or response format. I usually recommend RAG for business use cases, which we will confirm during the architecture phase.
Do you build the frontend user interface as well?
Yes. I am a Full-Stack developer. While I build the secure AI logic using Python/FastAPI or Node.js, I also build highly responsive, custom web interfaces for your AI using React, Next.js, and Tailwind CSS.
