Available for Senior Roles & Consulting

MUHIB AL HASAN

Software Engineer - Full Stack & Distributed Systems

I specialize in backend architecture, distributed systems, data-intensive applications, and cloud infrastructure, with full-stack experience when product requirements demand it. I build high-throughput systems and multi-tenant SaaS platforms focused on production reliability.

// work history

Experience

Feb 2026 – PresentDubai, UAE | RemoteCurrent

Software Engineer · Orexza

Architecting a high-scale multi-tenant SaaS platform for Shopify merchants featuring PostgreSQL schema isolation, event-driven background aggregation pipelines, and comprehensive OpenTelemetry observability.

PostgreSQLShopify APIRedisOpenTelemetryGrafana AlloyPrometheusLokiTempoFastAPIDocker
May 2024 – Jan 2026San Francisco, USA | Remote

Software Engineer II · UJET.CX

Promoted SE I → SE IISev-0 Mitigated

Engineered high-throughput features in a multi-tenant Rails monolith supporting 100k+ concurrent users with zero downtime. Promoted to SE II after leading critical incident mitigations on GKE that resolved a Google Code Red state and protected key enterprise contracts.

Ruby on RailsKubernetes (GKE)Google Cloud (GCP)MySQLRedisSidekiqGitLab FlowGitHub ActionsMicroservicesDistributed Systems
Apr 2023 – Aug 2023Dhaka, BD | Contractual

Software Engineering Lead · National River Conservation Commission

Led a 5-engineer team to design and deliver a nationwide incident reporting ecosystem spanning a public mobile app, investigator tools, and administrative panel on AWS.

Node.jsNext.jsReact NativeMySQLAWS EC2AWS S3REST APIs
// featured systems

Project Showcase

High-impact mobile applications, scalable cloud backends, government reporting systems, and automated scheduling engines.

Android & iOS Mobile ApplicationRelease: 2025

Chic Le Frique

High-performance e-commerce mobile application engineered for a premier Shopify store, delivering a fluid mobile retail experience on both Android and iOS.

Role & Contribution:Mobile Application Developer

Engineered the app architecture from ground up, implemented core e-commerce interactions, and integrated Shopify Storefront APIs with secure checkout and catalog caching.

Problem: A premier Shopify e-commerce brand needed a high-performance, native mobile presence to increase customer retention and reduce cart abandonment on both Android and iOS.

Architecture: Engineered a cross-platform React Native application directly integrated with the Shopify Storefront GraphQL API.

Technical Decisions: Utilized Redux/Context for optimized shopping cart state synchronization. Implemented aggressive image caching and pagination to handle large product catalogs seamlessly.

Outcomes: Delivered a fluid, responsive native retail experience with secure checkout, successfully published to major app stores, leading to increased mobile conversions.

Technologies Used

React NativeShopify Storefront APITypeScriptRedux / ContextREST APIs
// System Architecture Diagram
                  graph TD
    %% Chic Le Frique Architecture
    subgraph Client [Client Side]
        App[React Native Mobile App\nAndroid & iOS]
        Redux[(Redux/Context\nState Sync)]
        Cache[Image & API Caching]
        App --> Redux
        App --> Cache
    end

    subgraph Backend [Backend Infrastructure]
        Shopify[Shopify Storefront API\nGraphQL]
        REST[Custom REST APIs\nNode.js]
    end

    subgraph External [External Services]
        Payment[Payment Gateway]
    end

    App -- GraphQL --> Shopify
    App -- REST --> REST
    Shopify --> Payment

    classDef client fill:#121212,stroke:#deec56,stroke-width:1px,color:#fff;
    classDef backend fill:#1a1a1a,stroke:#38bdf8,stroke-width:1px,color:#fff;
    
    class App,Redux,Cache client;
    class Shopify,REST backend;
                
Government Water Resource Reporting EcosystemRelease: 2023

Amar Nodi (My River)

A nationwide dual-mobile app and web administration platform funded by the Bangladesh government for citizens and field investigators to report, verify, and resolve water resource issues.

Role & Contribution:Full-Stack Developer & Team Lead

Led a 5-engineer team to architect the complete 60+ endpoint backend REST service and developed core native mobile modules.

Problem: The national government lacked a centralized, real-time ecosystem for citizens to report water resource violations (pollution, encroachment) and for field officers to track resolutions.

Architecture: Designed a multi-client ecosystem with two React Native apps (Citizen & Investigator) communicating with a Node.js/Express Backend and a MySQL database deployed on AWS EC2.

Technical Decisions: Implemented geospatial queries using Google Maps API for precise incident mapping.

Outcomes: The platform was successfully completed and delivered to the government.

Technologies Used

React NativeNode.jsExpress.jsMySQLAWS (EC2)Google Maps API
// System Architecture Diagram
                  graph TD
    %% Amar Nodi Architecture
    subgraph Mobile Apps
        Citizen[Citizen App\nReact Native]
        Investigator[Investigator App\nReact Native]
    end

    subgraph AWS Cloud [AWS Cloud Infrastructure]
        Backend[Node.js / Express Backend\nEC2 Instances]
    end

    subgraph Third Party
        Maps[Google Maps API]
    end

    Citizen -- HTTPS --> Backend
    Investigator -- HTTPS --> Backend
    
    Citizen -- Direct Upload --> Backend
    Investigator -- Direct Upload --> Backend
    
    Citizen -.-> Maps
    Investigator -.-> Maps
                
Movie & TV Metadata Aggregation SystemRelease: 2019

ISP_FTP

A Python/Django-based media catalog and automation system designed to reduce manual work in building a structured movie and TV-series library by crawling remote media directories, extracting titles, and automatically enriching them with IMDb metadata and artwork.

Role & Contribution:Backend Engineer

Built a Django web application around a reusable media-ingestion backend. Implemented recursive parsing of remote media directories, automated poster retrieval, and IMDb integration.

Problem: Building structured media libraries from raw remote directories is highly manual and time-consuming without automated metadata extraction.

Architecture: Remote media directories are parsed via BeautifulSoup/lxml, titles are extracted, enriched via IMDbPY, downloaded via Pillow, and stored in Django ORM with SQLite.

Technical Decisions: Utilized Django ORM and SQLite for structured persistence, decoupled the automated ingestion endpoint from the presentation layer, and implemented robust fallback handlers for missing artwork.

Outcomes: Delivered a fully functional media catalog system with separate modules for movies and TV shows, enabling single-click ingestion from remote media servers.

Technologies Used

PythonDjango 2.2Django ORMSQLiteIMDbPYBeautifulSouplxmlPillowBootstrap
// System Architecture Diagram
                  graph TD
    %% ISP_FTP Architecture
    subgraph Ingestion [Ingestion Pipeline]
        Crawl[Remote Media Directories]
        Parse[URL/HTML Parser\nBeautifulSoup / lxml]
        Extract[Filename & Title Extraction]
        IMDb[IMDb Metadata Enrichment\nIMDbPY]
        ImageDL[Image Download\nPillow]
    end

    subgraph Storage [Persistence Layer]
        ORM[Django ORM]
        SQLite[(SQLite Database)]
        Media[(Local Media Storage)]
    end

    subgraph Frontend [Web Interface]
        DjangoViews[Django Views & Templates]
        UI[Movie/TV Web Interface\nBootstrap 4]
    end

    Crawl --> Parse
    Parse --> Extract
    Extract --> IMDb
    IMDb --> ImageDL
    ImageDL --> ORM

    ORM --> SQLite
    ORM --> Media

    SQLite --> DjangoViews
    Media --> DjangoViews
    DjangoViews --> UI
    
    classDef pipeline fill:#1a1a1a,stroke:#deec56,stroke-width:1px,color:#fff;
    classDef db fill:#121212,stroke:#38bdf8,stroke-width:1px,color:#fff;
    
    class Crawl,Parse,Extract,IMDb,ImageDL pipeline;
    class SQLite,Media db;
                
// research and writing

Publications

ResearchGate Profile
Paper 01November 2022

A Novel Method for Imbalanced Data Classification based on Label Reassignment

Ahmed Shabab Noor, Afsana Airin, Rezab Ud Dawla, Ahmed Rafi Hasan, Muhib Al Hasan, Akib Zaman, Dewan Md. Farid
TENCON 2022 - 2022 IEEE Region 10 Conference (TENCON)
Hong KongIEEE

Proposes a novel Label Reassignment approach designed to tackle class-imbalance in classification by reassigning majority class instances in overlapping decision boundaries to the minority class. Empirical results demonstrate significant improvements over SMOTE in Recall and F1-Score.

Imbalanced DataLabel ReassignmentMachine LearningDecision BoundariesSMOTEClassification
Paper 02December 2022

Attention-Based Scene Graph Generation: A Review

Muhib Al Hasan, Ahmed Rafi Hasan, Akib Zaman, Dewan Md. Farid, Afsana Airin, Rezab Ud Dawla, Ahmed Shabab Noor
2022 14th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)
Phnom Penh, CambodiaIEEE

A thorough systematic review and comparative analysis of recent attention-based methodologies in Scene Graph Generation (SGG). Evaluates object relation detection, graph neural networks (GNNs), visual relationship predicates, and perceptual scene comprehension with context-aware attention mechanisms.

Scene Graph GenerationAttention MechanismsComputer VisionGraph Neural NetworksVisual Relations
Paper 03September 2022

The Impact of Data Locality on the Performance of Cluster-Based Under-Sampling

Ahmed Shabab Noor, Muhib Al Hasan, Ahmed Rafi Hasan, Rezab Ud Dawla, Afsana Airin, Akib Zaman, Dewan Md. Farid
Machine Intelligence and Emerging Technologies (MIET 2022) / LNICST Vol. 490
Noakhali, BangladeshSpringer Nature

Investigates the role of spatial data locality and density clustering on the stability of under-sampling methods for highly skewed datasets, demonstrating empirical gains in decision boundary preservation and minority class recall using cluster-based under-sampling and ensemble learning.

Data LocalityCluster-Based Under-SamplingClass ImbalanceEnsemble LearningSupervised Learning
// academic background

Education

BRAC UniversityOct 2025 – Present

Master of Science in Computer Science and Engineering

Major: Data Science
United International UniversityJan 2019 – Jan 2023

Bachelor of Science in Computer Science and Engineering

Major: Data Science
Feni Computer InstituteAug 2014 – Jul 2018

Diploma in Engineering

Major: Data Telecommunications & Networking Technology
// technical expertise

Systems & Architecture

Distributed Systems

Event-Driven Architecture3+ yrs
Microservices3+ yrs
Distributed Processing2+ yrs
System Reliability2+ yrs

Backend

Ruby on Rails2+ yrs
FastAPI (Python)2+ yrs
Node.js / Express3+ yrs
API Architecture3+ yrs

Data

PostgreSQL3+ yrs
Redis3+ yrs
MySQL3+ yrs
Database Architecture3+ yrs

Cloud & Infrastructure

GCP & AWS2+ yrs
Kubernetes (GKE)1+ yrs
Docker3+ yrs
CI/CD & Automation1+ yrs

Observability

OpenTelemetry1+ yrs
Prometheus & LGTM1+ yrs
// direct reach

Contact

Open to senior backend, distributed-systems, platform, and software-architecture opportunities.

Phone
+8801736480320