Agentic AI architectures
Multi-step agents with tools, memory and evaluation loops — LangGraph over ad-hoc chains.
Open to opportunities
Designing intelligent software.Engineering exceptional experiences.
I build agentic AI systems and production full-stack products — LangChain and LangGraph workflows, RAG pipelines, and Next.js applications that hold up outside a demo.
- Role
- AI Full Stack Engineer
- Based in
- Lahore
- Focus
- Agentic AI
Abdul Wahid
AI Full Stack Engineer
01Selected Work
Four builds.Four different problems.
An agent that answers customers on WhatsApp, a realtime dispatch platform, a travel planner, and a vision pipeline with no model in it. Each one has a full case study.
- 01
AI Chatbot for Small Businesses
Self-hosted WhatsApp agent
n8nMeta WhatsApp Business APIOllama - 02
RideConnect
Real-time ride-sharing platform
Next.jsNode.jsMongoDB - 03
TravelSync
Travel planning platform
Next.jsMongoDB AtlasAuth.js (NextAuth v5) - 04
Vehicle Detection & Traffic Analysis System
Classical computer vision
MATLABImage ProcessingCLAHE
02About
I care about the wholesystem, not just the model.
I’m a Computer Science undergraduate at the University of Management & Technology, Lahore, and I’ve spent the last two years doing the same thing in two different directions: shipping full-stack products, and teaching machines to act inside them.
That combination is deliberate. Most AI work fails not because the model is wrong, but because nobody engineered the system around it — the retrieval, the state, the failure paths, the interface a real person actually touches. I’d rather own that whole surface.
- Engineering internships
- 2Engineering internshipsAI and full-stack
- CGPA / 4.00
- 3.55CGPA / 4.00B.S. Computer Science
- Team led as Project Lead
- 3–5Team led as Project LeadFraternity, UMT
03Current Focus
What I’m deliberatelygetting better at.
Three things I’m working on right now, chosen because they’re the difference between building something that demos and something that runs.
AWS & system design
Moving from 'it deploys' to 'it scales' — services, queues, and failure boundaries.
Vector databases
Retrieval quality as an engineering problem: chunking, embeddings, and ranking.
Working toolset
LangGraphLangChainOpenAI APIsRAGNext.jsTypeScriptNode.jsMongoDBPineconeDockern8nOllamaPythonVercelLangGraphLangChainOpenAI APIsRAGNext.jsTypeScriptNode.jsMongoDBPineconeDockern8nOllamaPythonVercel
04 — Contact
Let’s build somethingmeaningful together.
Available for AI engineering and full-stack roles, internships, and freelance work — remote or Lahore-based.