Taste is a delivery tool
Interfaces, APIs, and deployment paths should feel composed because good judgment reduces the number of decisions a client has to carry.
Backend systems, cloud architecture, data pipelines, and full-stack products. Built inside Paytm, Travelopia and now through Madian.
Ameen’s work sits at the intersection of product taste, resilient backend systems, and calm delivery.
Interfaces, APIs, and deployment paths should feel composed because good judgment reduces the number of decisions a client has to carry.
The work favors focused scopes, clear architecture, and pragmatic automation so a lean product team can move with senior-engineering confidence.
A build is not complete when it looks good locally. It needs observability, handoff clarity, and a path for the next iteration.
Each stint produced systems that had to keep running after the handover.
2025 - Present
ConsultancyI take on backend platforms for early SaaS products and membership or community portals for media and non-profit clients. Most engagements are solo or small team, with delivery windows that need a senior engineer who can move from architecture into code without ceremony. The infrastructure mix runs from full serverless to long-running servers, picked to match what each workload actually needs.
2025 - 2025
Full-timeA short engagement with a health-tech engineering team focused on a document delivery service that was running into throughput limits. The work was about tightening the PDF generation path so the team could move past a production bottleneck.
2022 - 2025
Full-timeMy team owned a serverless ETL platform that moved data between operational systems and the products that lived downstream. I built and maintained the pipelines that did most of the heavy lifting, designed the cloud architecture in infrastructure as code, and over time worked the platform towards better processing efficiency and lower infra cost. I also spent a fair amount of time helping newer engineers find their footing on the team.
2019 - 2022
Full-timeI led backend work on the travel platform during a stretch where we were pulling apart a long-standing monolith into smaller, more focused services. Most of the new services were built in Python and Node.js. I covered for the tech lead during their absence, kept the team unblocked, and onboarded new engineers as they joined. A good chunk of the year went into stabilising a high-traffic Express service and reworking the booking retry flow so conversions held up under load.
I worked across data, services, and search for the booking platform. The data pipelines automated delivery from operational stores into the analytics warehouse. The microservices powered things like ML training and personalisation features. On the booking side, I hardened the flows with durable queueing so messages stayed reliable, and I made customer-facing search behave more sensibly when names came in with regional spelling variation.
2018 - 2018
InternshipA short internship where I designed, built, and shipped a carpooling web app on Python and Django end to end. I owned the project on my own, and it was a useful first pass at running a real deployment.
A VS Code extension that streamlines Python Poetry monorepo development by automatically setting the correct interpreter and paths for LSP support.
An interactive virtual platform for a historical exhibition, featuring a Flutter app, rich animations, a headless CMS, and backend infrastructure.
A graduation project that recognizes user activities in real time using smartphone sensor data processed by a machine-learning backend server.
A web application for Withdraw EIA 2020 that generated customized mass emails with unique body content and handled high-volume public use.
The base that everything else compounds on — algorithms, systems, and applied ML, learned in a four-year engineering program.
Govt. Model Engineering College
Software engineering, systems thinking, and applied machine learning.
Graduation project | Situation Sensitive Activity Recognition: Real-time activity inference from smartphone sensors backed by Artificial Intelligence.