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Kamran M. Node.js, AWS and Microservices

My name is Kamran M. and I have over 4 years of experience in the tech industry. I specialize in the following technologies: GraphQL, Python, NestJS, Node.js, AWS Lambda, etc.. I hold a degree in Bachelor of Science (BS), High school degree. Some of the notable projects I've worked on include: AWS CDK - Agentic WebClassifier, Confluence - secure RAG within AWS with Amazon Connect, Serverless Multi-Agent RAG - MCP Solution within AWS, AWS Textract Workflow. I am based in Lahore, Pakistan. I've successfully completed 4 projects while developing at Softaims.

My passion is building solutions that are not only technically sound but also deliver an exceptional user experience (UX). I constantly advocate for user-centered design principles, ensuring that the final product is intuitive, accessible, and solves real user problems effectively. I bridge the gap between technical possibilities and the overall product vision.

Working within the Softaims team, I contribute by bringing a perspective that integrates business goals with technical constraints, resulting in solutions that are both practical and innovative. I have a strong track record of rapidly prototyping and iterating based on feedback to drive optimal solution fit.

I'm committed to contributing to a positive and collaborative team environment, sharing knowledge, and helping colleagues grow their skills, all while pushing the boundaries of what's possible in solution development.

Main technologies

  • Node.js, AWS and Microservices

    4 years

  • GraphQL

    1 Year

  • Python

    3 Years

  • NestJS

    2 Years

Additional skills

Direct hire

Potentially possible

Previous Company

Fiverr

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Experience Highlights

AWS CDK - Agentic WebClassifier

Built scalable web content classifier using ReactJS frontend + AWS serverless backend. System processes URLs through Lambda workflow: job management, AI-powered classification via Bedrock, automated r

Confluence - secure RAG within AWS with Amazon Connect

Built serverless architecture integrating Confluence docs with AI processing pipeline. Features: automated content ingestion via Event Bridge, Lambda-based processing, DynamoDB storage, S3 data lake,

Serverless Multi-Agent RAG - MCP Solution within AWS

Designed & implemented a sophisticated multi-agent AI system that orchestrates 7+ specialized agents to gather, process & synthesize data from diverse sources (CRM, web, social media, databases). Feat

AWS Textract Workflow

I have to setup a pipline and workflow with followings: 1. Email will be received to the client specifics emails with some Attachements. 2. Above received email will also be received in AWS S3 via AWS

Education

  • University of the Punjab

    Bachelor of Science (BS) in Computer science

    2017-01-01-2021-01-01

  • Government College University, Lahore

    High school degree in Computer science

    2015-01-01-2017-01-01

Languages

  • English (Fluent)✓