Capabilities, architecture, and evidence.
How I contribute to an engineering team or product — a practical map of backend development, data, infrastructure, delivery and architecture.
What I do
Backend Engineering
Production-ready backend systems using Laravel/PHP, Node.js and TypeScript — APIs, business logic, authentication, integrations and database architecture.
Data & Infrastructure
Data modeling and the infrastructure that runs the systems — MySQL, MongoDB, Redis caching, containers and cloud servers.
Delivery & DevOps
Containerizing applications, building deployment workflows, configuring Linux environments and improving delivery reliability.
System Architecture
Turning requirements into maintainable architectures, modular systems, service boundaries and deployment strategies.
Frontend & Mobile
Building clean interfaces and mobile apps — Vue.js, Nuxt.js, Next.js, JavaScript and TypeScript, with Flutter for mobile.
What has shipped together.
Select a technology to see what it has actually been used alongside, across real projects and roles.
- MongoDB
- Firebase
- Database Design
- GraphQL
AI in my practice
AI-Assisted Development
I use AI coding tools daily — AI agents, Copilot, ChatGPT and Claude — to develop, debug, review, document and test software. AI is part of my normal engineering workflow.
AI Application Engineering
I have shipped a production AI/LLM integration and I work across the layer it lives on: backend APIs, authentication, Redis caching, queues and async jobs.
Backend & AI Infrastructure
Docker, Kubernetes, cloud servers and DevOps are exactly what it takes to package, deploy and operate AI-powered services reliably.
Currently Exploring
LLM application architecture · RAG · AI agents · vector search · MCP servers · AI observability and evaluation.
Where I fit in an AI-driven engineering team
My value isn't simply knowing how to call an LLM API. It's the production backend, data, infrastructure and deployment that make AI features real — plus the ability to integrate the AI layer itself.
Each layer below is a capability I bring from shipping production systems. The AI application layer is where I'm actively building.
Where I'm going
How production systems are put together
The pattern I build toward: an application layer over clear service boundaries, backed by durable data and wrapped in containerized, observable delivery.
Detailed engineering work
Integrated Digital Service Delivery Platform
Microservice-based digital service delivery platform for the Ministry of Chittagong Hill Tracts Affairs.
Online Exam & Certificate Management System
Online exam and certificate management system for the Department of Shipping, built with PHP, Laravel and Next.js.
DLS Automation System
Microservice automation platform for the Department of Livestock Services, built with PHP, Laravel, Vue, Nuxt and Node.js.