About me
I build and run e-commerce platforms, multi-tenant SaaS and hardware-connected systems
— plus the UAV and aerospace work I research and teach.
Experience
Building the backbone of modern AI—delivering production-grade systems with mathematical rigor and operational excellence
- 2020 – Present
Senior Software Engineer [ Orbitronix Technologies ]
Building and operating e-commerce platforms, multi-tenant SaaS, agritech automation (FarmOS Pulse) and robotics systems for clients in the US, UK and Bangladesh.
- 2019 – Present
Technology & Strategy Architect [ SwaggerBrand, New Orleans ]
Engineering for the agency's US clients: inspection SaaS, GoHighLevel lead funnels, consent-mode compliance and technical SEO.
- 2022
Aerospace Researcher [ IAC 2022, Paris ]
Presented research on modelling and validating the Moon's radiation environment at the 73rd International Astronautical Congress.
- Ongoing
STEM Educator & Workshop Lead [ Space Camp India ]
Workshops on UAV fabrication, quadcopter building for hobbyists, rocket propulsion, sugar rockets and CanSat design; mentors UAV and autonomous-swarm teams.
- 2020
B.Tech [ Computer Science & Engineering ]
Bachelor of Technology in Computer Science & Engineering.
My Process
I integrate deep architectural research, rigorous data strategy, and production engineering to build resilient AI systems.
01. System Audit & Discovery
I begin with an in-depth audit of your data landscape, current infrastructure, and core business objectives. This foundational phase identifies technical constraints and sets the architectural direction for the project.
02. Architectural Strategy
Together, we develop a comprehensive technical roadmap. I design the neural architecture and data flow, establishing clear performance benchmarks—such as latency thresholds and accuracy targets—required for success.
03. Engineering & Deployment
The development phase moves through focused sprints of training, fine-tuning, and rigorous testing. I transform theoretical designs into scalable, production-grade AI models integrated into your live environment.
04. MLOps & Evolution
Post-deployment, I implement continuous monitoring and MLOps pipelines to prevent model drift. We constantly measure and refine the system, ensuring the AI remains accurate and scalable as your data demands evolve.
Tech Stack / Tools
The stack I ship to production, plus the hardware tools behind my UAV and PCB work.
Languages
PHP
TypeScript
JavaScriptBackend
Laravel
Node.js
Next.js
Frontend
Vue
React
TailwindData & Infra
MySQL
PostgreSQL
nginx
Hardware
KiCad
Arduino
LinuxFrequently Asked Questions
Your questions about my process, services,
and workflow—answered.
E-commerce platforms, multi-tenant SaaS, payment, courier and ad-tracking integrations, and hardware-connected systems - designed, built, deployed and run in production. On the hardware side: UAV avionics and PCB design.
With an audit of the existing hardware, data and infrastructure. Constraints get mapped and the architecture agreed before any code is written.
Bangladesh, working remotely with clients in Europe and North America - taking projects from the first architecture decision through to a running production deployment.
You do. Codebase, infrastructure and documentation transfer in full at the end of the engagement. No vendor lock-in.