sarfaraz@matrix: ~/portfolio — zsh — 80x24

Sk Sarfaraz Ahamed — Senior Software Engineer / Full Stack Developer Portfolio

Sk Sarfaraz Ahamed is a Senior Software Engineer based in Mumbai, India, with 4+ years of experience building full-stack web applications. Skills include TypeScript, React, Next.js, NestJS, Node.js, Python (FastAPI, Django, Flask), REST APIs, AWS (Lambda, S3, EC2, SQS, API Gateway), GCP, Docker, and applied LLM / RAG / Vector Database work. Currently SDE-II at Data Sutram. Reach out: sksarfaraz4006@gmail.com.

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sarfaraz@matrix:~$ whoami
Sk Sarfaraz Ahamed
name
Sk Sarfaraz Ahamed
role
Senior Software Engineer / Full Stack
experience
4+ years
location
Mumbai
email
github
linkedin
status
[OPEN TO WORK]
sarfaraz@matrix:~$ cat summary.md
# Summary

Senior Software Engineer with 4+ years building full-stack apps that scale. I work across the stack — building clean React and Next.js UIs on the front, and reliable APIs in NestJS, Node.js, and Python (FastAPI, Django) on the back.

I ship microservices on AWS and GCP, tune databases like PostgreSQL and MongoDB, and plug in GenAI / LLM features when they make sense. I like fast-moving teams and turning rough ideas into working products people can use.

sarfaraz@matrix:~/experience$ git log --oneline
Software Development Engineer II — Data Sutram
  • Own features end to end: ship full-stack features in TypeScript, React (Next.js) on the front, and NestJS / Node.js / Python on the back. Focus on speed, accessibility, and scale.
  • Scalable architecture: built and deployed microservices and serverless functions on AWS Lambda + API Gateway that handle heavy traffic.
  • Infra & security: used Docker to set up infra and run services locally. Added login with OAuth2, JWT, and role-based access (RBAC).
  • Data & observability: used AWS S3 and SQS to run reliable async jobs and keep services observable.
  • Team work: worked closely with Product, QA, and DevOps in agile sprints. Ran code reviews, kept docs (DFDs) updated, and wrote Jest unit/integration tests.
TypeScriptReactNext.jsNestJSPythonAWS LambdaDockerOAuth2Jest
Software Development Engineer I — Data Sutram
  • Full-stack product work: built user-facing features in React and Next.js, plus server APIs in Python (FastAPI) and Node.js.
  • Made it faster: profiled DB queries and API response times to cut latency and make pages feel snappier.
  • Data pipelines: built scrapers and ingestion pipelines to pull and clean external data for analytics features.
  • Cloud deploys: handled deploys and hosting on AWS EC2, S3, and Lambda.
ReactNext.jsPythonFastAPINode.jsAWS EC2S3Lambda
Software Developer Internship — Data Sutram
Worked with the core product team to build and improve reusable web UI parts in React.js and Next.js. Managed app code and state through GitHub.
React.jsNext.jsGitHub
Full Stack Developer Internship — Mirror Score
  • Built clean, easy-to-maintain REST APIs in Python (Django). Plugged in Google APIs and wrote automation scripts.
  • Built UIs in ReactJS and packaged services with Docker and AWS.
PythonDjangoReactJSDockerAWS
sarfaraz@matrix:~$ cat education.txt
degree
Bachelor of Computer Application
institute
Techno International New Town
location
Kolkata, India
duration
Jul 2019 — Jun 2022
sarfaraz@matrix:~/skills$ ls -la
front-end/
  • JavaScript
  • TypeScript
  • React.js
  • Next.js
  • Redux
  • HTML5 / CSS3
  • Electron
  • jQuery
  • Design Systems
back-end/
  • Python
  • FastAPI
  • Django
  • Flask
  • Selenium
  • Node.js
  • NestJS
  • REST APIs
ai_engineering/
  • LLMs (ChatGPT, Claude)
  • Copilot
  • RAG
  • Vector Databases
  • Model Fine-Tuning
cloud_devops/
  • AWS EC2
  • AWS S3
  • AWS Lambda
  • AWS SQS
  • API Gateway
  • GCP
  • Docker
  • Linux
  • GitHub CI/CD
sarfaraz@matrix:~/projects$ cat *.json
MeetRead AI
MeetRead joins your Google Meet calls, records audio, captures transcripts, and writes summaries — without sending your data anywhere you don't control.
ElectronPythonLLMsTranscriptsSelf-hosted
AI Engineering Ecosystems
Building small apps that use RAG (Retrieval-Augmented Generation) and vector databases to read and make sense of messy multimedia metadata.
RAGVector DBLLMsPython
sarfaraz@matrix:~$
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