Build With Moenu buildwithmoenu.com
About

The resume, with the actual person still intact.

I moved from IIT Kharagpur to New York, spent years in enterprise and Amazon-scale systems, and then stepped into a builder phase where product conviction and ownership matter more than looking conventionally impressive.

Ahmad with Oscar
Three-act arc

India, New York, then the builder phase.

India · 2013–2021

Foundation

IIT Kharagpur Electrical Engineering, KVPY scholar. Then Loylty Rewardz in Mumbai, leading a batch→Kafka migration on a loyalty engine processing millions of transactions a day. First real production chops.

NYC · 2021–2025

Enterprise

NYU Tandon MS. Then Amazon Ads — Java/Python microservices powering international marketplace expansion, multi-region AWS at 99.9%+ availability. Learned distributed-systems discipline. Learned advertising wasn't the product I wanted to build.

Now · Sep 2025 → present

Builder

Walked away from comp. Two live freelance sites. Two AI products. Selective with what's next.

Start from problems, not tech stacks. Don't just write code — ship products.
Resume structure

The formal story and the current one are finally aligned.

Experience

The work history, chronologically.

Amazon-scale systems, enterprise backend foundations, and then a builder phase where product taste started to matter as much as technical depth.

2021–2025 · NYC

Software Development Engineer · Advertising

Amazon
  • Ad delivery services that scaled to international markets without sacrificing latency budgets.
  • Distributed-systems discipline at Amazon scale — caches, queues, retries, observability.
  • Left when the technical complexity stopped translating into product I cared about.
2018–2021 · Mumbai

Software Engineer

Loylty Rewardz
  • Apache Camel + Kafka pipelines replacing fragile batch jobs.
  • First real ownership over production systems people actually depended on.
Education

IIT Kharagpur and NYU Tandon are both in the wiring.

NYU Tandon School of Engineering

MS, Electrical Engineering

ML, Deep Learning, Big Data coursework.

IIT Kharagpur

BTech, Electrical Engineering

Computer Vision, IoT projects. KVPY scholar.

Working mode

The way I work now.

I like end-to-end ownership, products with a real point of view, and systems where the operational details are part of the product rather than hidden behind it.

Skills

The stack is wide because the work has been end to end.

Languages
JavaPythonJavaScriptTypeScriptSQL
Backend
Node / ExpressSpringApache KafkaApache Camel
Frontend
ReactNext.jsvanilla JS when it's the right call
AI / ML
LangChain patternsReAct loopsMCPMulti-provider routingSentence-transformerspgvector retrieval
Data
Parquet
Ops
AWS (Amazon scale)NginxLet's EncryptDeploy pipelines you can hand off
Builder bias

The throughline is not “full stack.”

It is owning enough of the product to make better decisions: backend systems, AI orchestration, interface quality, deployment, and the narrative layer people actually experience.