Fahim Shahriar Anik here—an experienced senior full-stack and data-focused software engineer with 9+ years delivering enterprise-grade, cloud-native systems across healthcare, telecom, and AI. I blend hands-on proficiency in Angular, Spring Boot, Python, Docker/Kubernetes, and cloud pipelines (AWS, Azure, GCP) to build scalable solutions and modernize legacy apps. I’ve led modernization efforts, optimized ML workflows, and shipped complex UI and backend features for production clients. I enjoy mentoring teammates, improving test coverage, and delivering robust CI/CD pipelines on AWS/Kubernetes infrastructure while advocating clean code, thoughtful design, and collaborative problem-solving.…

Fahim Shahriar Anik

Fahim Shahriar Anik here—an experienced senior full-stack and data-focused software engineer with 9+ years delivering enterprise-grade, cloud-native systems across healthcare, telecom, and AI. I blend hands-on proficiency in Angular, Spring Boot, Python, Docker/Kubernetes, and cloud pipelines (AWS, Azure, GCP) to build scalable solutions and modernize legacy apps. I’ve led modernization efforts, optimized ML workflows, and shipped complex UI and backend features for production clients. I enjoy mentoring teammates, improving test coverage, and delivering robust CI/CD pipelines on AWS/Kubernetes infrastructure while advocating clean code, thoughtful design, and collaborative problem-solving.…

Available to hire

Fahim Shahriar Anik here—an experienced senior full-stack and data-focused software engineer with 9+ years delivering enterprise-grade, cloud-native systems across healthcare, telecom, and AI. I blend hands-on proficiency in Angular, Spring Boot, Python, Docker/Kubernetes, and cloud pipelines (AWS, Azure, GCP) to build scalable solutions and modernize legacy apps. I’ve led modernization efforts, optimized ML workflows, and shipped complex UI and backend features for production clients.

I enjoy mentoring teammates, improving test coverage, and delivering robust CI/CD pipelines on AWS/Kubernetes infrastructure while advocating clean code, thoughtful design, and collaborative problem-solving.

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Skills

Experience Level

Python
Expert
Docker
Expert
JavaScript
Expert
AWS
Expert
SQL
Expert
Spring
Expert
React JS
Expert
PyTorch
Expert
Node.js
Expert
Kubernetes
Expert
Java
Expert
AngularJS
Expert
TypeScript
Expert
TensorFlow
Expert
MySQL
Expert
PostgreSQL
Expert
Django
Expert
Google Cloud
Expert
Azure
Expert
Snowflake
Expert
GitHub CoPilot
Expert
React Native
Expert
Oracle
Expert
Selenium
Expert
Redis
Expert
CSS
Expert
Data Visualization
Expert
GraphQL
Expert
Elasticsearch
Expert
MongoDB
Expert
Microsoft SQL
Expert
Keras
Expert
Jira
Expert
HTML5
Expert
Hadoop
Expert
Go
Intermediate
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Language

English
Fluent

Work Experience

Senior Full Stack Developer at Clean Code Limited
April 1, 2025 - October 27, 2025
Led Angular 12→19 migration for Health Standards Organization enterprise app; managed 5 developers; reduced build time by 40%. Oversaw CI/CD and Docker-based deployments on AWS Kubernetes clusters, improving rollout consistency by 30%. Mentored junior engineers and conducted peer code reviews to improve frontend architecture and test coverage.
Software Developer at IBM
April 1, 2025 - April 1, 2025
Member of CAMS (Cloud AI Management Services) team powering WatsonX data operations. Refactored core Java API (600 lines, +JUnit coverage) boosting throughput ~1%. Contributed to migration from NoSQL (CouchDB) to PostgreSQL with schema validation and data migration scripts. Closed 15 production issues and 10 client tickets via container and RabbitMQ optimizations. Enhanced Jenkins pipelines with SonarQube PR quality gates.
Full Stack Developer (Contract – Part Time) at Clean Code Limited / HSO Client
April 1, 2024 - April 1, 2024
Co-built the Attestation feature, a core work stream (~1/3 of HSO app usage; ~20K LOC across Angular + Spring Boot). Developed Excel export module introducing 3 new REST APIs, dynamic SQL queries; improved data latency by 25%. Resolved 50+ defects and created visitor-pattern REST endpoints to simulate web socket behavior for real-time updates.
Software Developer at Bell Canada
April 1, 2024 - April 1, 2024
Refactored legacy Python analytics web app using Flask/Django; added typing safety and better modularity. Implemented ELK pipeline + ETL Airflow jobs (GCP) handling multi-million-row datasets; cut query latency by 60%. Built ML prediction model for missing data using Hugging Face and SHAP for explainability — accuracy +7%.
Machine Learning Engineer at Ask Polly
July 31, 2022 - July 31, 2022
Applied fuzzy c-means clustering to rank companies within geo regions. Performed data scraping/cleaning in Python & R; visualized results with JavaScript dashboards. Deployed ML workflows on Kubernetes; demonstrated interpretability and deployment readiness.
Software Engineer at Therap Services LLC
August 1, 2018 - March 14, 2021
● Built a Training Management System (TMS) using React (v15–16) and Spring Boot, developing reusable class-based components, lifecycle logic (componentDidMount, shouldComponentUpdate), and REST APIs for course, schedule, and user modules. ● Engineered backend workflows in Spring Boot for date normalization, date pickers, session scheduling, and multi-tab edit blockers using transactional locks and concurrency-safe entity updates. ● Optimized UX by migrating legacy jQuery UIs to React components, implementing lazy loading, debounced inputs, and role-based access via Spring Security with JWT authentication.

Education

M.Eng. Electrical and Computer Engineering with Interdisciplinary AI at University of Ottawa
January 1, 2011 - December 1, 2022
Bachelor of Science in Electrical and Electronics Engineering at BRAC University
September 1, 2013 - April 1, 2018

Qualifications

Add your qualifications or awards here.

Industry Experience

Healthcare, Software & Internet, Professional Services, Telecommunications, Government, Media & Entertainment, Education
    paper Lead Developer Haus of Axion

    Haus of Axion — Overview

    Haus of Axion is a premium fitness and lifestyle platform that combines elite in-home personal training, hybrid athletic programming, and tech-enabled client experiences.
    It is designed for high-performing professionals, bridal clients, and lifestyle-focused individuals who want luxury, accountability, and results—without the friction of traditional gyms.

    The brand positions itself at the intersection of high-touch concierge services and scalable digital fitness infrastructure.

    Haus of Axion App — Key Features

    1. Client Experience
      Secure user onboarding & profiles
      Fitness goals, injuries, preferences tracking
      Personalized training plans
      Workout history & progress tracking
      Media uploads (progress photos, form videos)
      In-app messaging with trainers
      Session booking & rescheduling
      Notifications & reminders

    Differentiation
    Luxury positioning (not mass-market fitness)
    High-touch concierge model
    Hybrid delivery (offline + online)
    Bridal & lifestyle specialization
    Founder-led quality control
    Scalable tech backbone from day one

    Tech Stack (Current & Planned)
    Frontend
    Web App
    Angular (latest stable)
    TypeScript
    Responsive UI (mobile-first)

    Backend
    API Layer
    Node.js / NestJS
    GraphQL (interactive, client-driven queries)

    Authentication
    Secure token-based auth
    Role-based access (client / trainer / admin)

    Database & Storage
    Primary Database
    PostgreSQL (hosted via Supabase)
    File Storage
    AWS S3 (user-uploaded media, progress photos, videos)

    Cloud & Infrastructure
    AWS
    Lambda (serverless backend)
    API Gateway (GraphQL & REST where needed)
    CloudWatch (logging & monitoring)
    Deployment
    CI/CD pipelines
    Frontend hosted via AWS Amplify
    Backend deployed via Serverless Framework
    Analytics & Observability
    Usage & engagement tracking
    Error monitoring
    Performance logging

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    paper AI Food Detection Gradle Project in Java

    Description:
    The Food Detection Gradle Project is a Java-based application that identifies and classifies food items using machine learning models. Built with a focus on modularity and scalability, this project integrates Gradle as the build automation tool and employs image recognition techniques to detect various food items. It showcases the combination of Java and AI in real-world applications.

    Key Features:

    Food Item Detection: Recognizes and classifies food items from images using trained models.

    Scalable Build System: Utilizes Gradle for dependency management and project organization.

    Seamless Integration: Designed for easy integration with existing Java projects.

    Customizable ML Model: Supports the use of custom-trained models for unique datasets.

    Cross-Platform Support: Runs efficiently on different platforms with Java runtime support.

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    paper AI Full Stack Project for Fruit and Vegetable Classification

    Description:
    Fruit and Vegetable Classification is a machine learning-based project that classifies fruits and vegetables using image recognition. It demonstrates the use of convolutional neural networks (CNNs) for accurate identification and categorization. Designed as a practical implementation of deep learning techniques, the project provides an engaging exploration of AI in the food industry.

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