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Mohammed Abul Fazal Fazlullah Sharief

Software Development Engineer​

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Summary​

Backend Engineer with a knack for building resilient, future-ready systems. I leverage Node.js, TypeScript, and AWS to create services that maintain their composure under pressure and adapt to evolving business needs. My approach combines technical expertise with practical foresight – designing APIs that developers actually want to use and infrastructure that doesn't wake up the on-call team. Coding isn't a joke, yet I write like one-if I have to explain it, it's bad. I find satisfaction in elegant solutions that balance performance needs with maintainability concerns, always considering how today's code decisions impact tomorrow's scaling challenges. Committed to continuous improvement because in backend engineering, the most impressive systems are the ones nobody notices until they're handling 10x the load they were built for. Designing Data Intensive Applications book is my professional holy scripture.

Skills​

  • Programming Languages: JavaScript, TypeScript, Python, Swift
  • Frameworks/Runtimes: NodeJS, Django, Flask, SwiftUI
  • Databases: DynamoDB, MongoDB, PostgreSQL, Redis, SQLite
  • Cloud Technologies: Amazon Web Services - EC2, ECS, S3, SQS, DynamoDB, Bedrock, Lambda, Aurora PostgreSQL Serverless, IAM
  • AI/ML: Retrieval Augmented Generation(RAG), Agentic Applications, Vector Embeddings, Vector Search
  • Tools: Git, Docker, Terraform
  • Methodologies: Agile, Scrum, Object-Oriented Programming (OOP)
  • Testing: Jest
  • Other: Problem-Solving, Communication, Teamwork

Experience​

  • Software Engineer | DAZN | June, 2024 - Present

    • Designed and built independently DAZN's first Large Language Model(LLM) application, leveraging generative AI with Retrieval Augmented Generation(RAG) using Vector Search, that provides real time analysis of customer support queries, therefore helping operations team derive strategies to resolve them quickly.
    • Implemented Parallel Computing in NodeJS to split thousands(140K+) of high computing tasks to complete it faster, reducing overall processing time from 24 hours to less than 5 hours.
    • Implemented Byte Order Mask(BOM), which persists bytes that identify encoding, for CSV files to persist UTF-8 encoding in applications like MS-Excel.
    • Setup SQS for consuming out of order messages via centralized streaming service based on SNS, and store it in DynamoDB.
    • Deployed Meta's Large Language Model, Llama 3.2, on AWS Bedrock and built AI writing assistant for agents.
    • Integrated a couple of HMAC(Hash-based Message Authenticated Code) APIs.

  • Junior Software Engineer | Vigocare | Dec, 2022 - June, 2024

    • Reduced a MongoDB collection query time from 45sec to 3sec just using projection option, saved 1000's of dollars in caching solution.
    • Developed, automated publishing, installation and deletion of a private npm package which resulted in 10x reduction in code repetition and bugs.
    • Integrated third party video calling service and developed all the APIs from scratch.
    • Migrated mongoose library for services from v5 to v8, that is 3 major upgrades.
    • Improved the performance of an API by 40x, reducing response size from 20MB to 500KB, that was bottlenecked by gRPC.
    • Contributed to iOS app occasionally and integrated Core Data and multiple new APIs.

  • Read more detailed experience in my Monthly Review.

Projects​

  • Yoga Pose Recommender: AI-Powered Vector Search for Yoga Poses | GitHub Repo

    • Built an AI-powered semantic search system that helps users explore yoga poses. By leveraging Gemini (LLM) to generate rich, context-aware descriptions and create high-dimensional vector embeddings, the project transforms an existing Hugging Face dataset into a deeply intelligent and intuitive search experience. With LangChain JS orchestrating data processing and Firestore serving as a high-performance vector database, users can retrieve the most relevant yoga poses through natural language queries. Additionally, Google Cloud’s Text-to-Speech technology enhances accessibility by providing immersive audio descriptions. Built with Node.js, this system seamlessly integrates AI-driven search, vector embeddings, and real-time query processing to redefine yoga exploration.

  • Source Crowd | GitHub Repo

    • Designed and built a web application using Django, where people post links to the webpages that they find helpful, and others can vote based on the quality. They can also add a title and description for that link, based on which others can search for that webpage. It's a crossover of Google Search and Reddit.

  • Command Line Generative AI | GitHub Repo

    • A command line generative AI bot that can be used directly from the terminal without the need for going to a browser. Utilizes Google's Large Language Model(LLM), Gemini Pro.

  • Network | GitHub Repo

    • A full-stack social networking site like Twitter, for making, deleting, and editing posts. Using Fetch API, implemented following features: like and unlike posts, and follow other users.

  • View all Projects.

Education​

Blogs​

Coursework​

Achievements & Activities​

  • Quizophos 2017 - Winner
    • A inter-college general quiz competition conducted by the Department of Mathematics.