Arshad Shaik

Cloud Developer | Software Engineer | AI/ML Specialist
1720 E Broadway Road, 85282, Tempe, US.

About

Highly accomplished Cloud Developer and Software Engineer with a Master's in Information Technology and a strong background in optimizing cloud infrastructure, enhancing backend performance, and developing AI/ML solutions. Proven ability to drive significant improvements in system throughput, reduce operational costs, and accelerate development cycles, as demonstrated by a 35% increase in Lambda throughput and 40% reduction in deployment errors. Adept at leveraging AWS services, microservices, and advanced testing methodologies to deliver robust and scalable software solutions.

Work

LEAP Consultants LLC (School Fuel)
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AWS Cloud Developer

Remote, US

Summary

Currently serving as an AWS Cloud Developer, Arshad Shaik optimizes cloud infrastructure and operations, driving significant improvements in system performance, cost efficiency, and reliability for critical applications.

Highlights

Improved Lambda throughput by 35% using AWS provisioned concurrency for concurrency controls and cold-start mitigation.

Reduced RDS query latency by 28% by refactoring queries and optimizing connection pooling with SQLAlchemy for PostgreSQL.

Achieved $2,000 monthly cost savings in S3 by implementing lifecycle policies and automated archival for infrequently accessed objects.

Enabled real-time alerting by integrating SES and CloudWatch for async job success and failure notifications.

Reduced deployment errors by 40% by refactoring Terraform IaC scripts and validating environment variables pre-deploy.

Capgemini Technology Services
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Software Engineer

Bangalore, India

Summary

As a Software Engineer at Capgemini Technology Services, Arshad Shaik enhanced backend performance and streamlined development processes, contributing to improved system efficiency and faster delivery cycles.

Highlights

Boosted backend performance by 45% through migrating monolithic modules to Spring Boot microservices with asynchronous communication.

Automated QA reporting process using Jenkins pipelines and SonarQube, reducing manual efforts by 60%.

Accelerated customer onboarding by 22% by redesigning account creation flow and caching frequent form metadata.

Reduced build pipeline duration by 33% by parallelizing unit and integration tests within CI/CD.

Enhanced test reliability by integrating Testcontainers and embedded PostgreSQL setups for robust service testing.

QSpyder's
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Test Automation Intern

Bangalore, India

Summary

As a Test Automation Intern at QSpyder's, Arshad Shaik identified critical bugs and optimized testing processes, significantly improving software quality and efficiency.

Highlights

Identified over 40 critical UI bugs pre-release by implementing Selenium-based visual regression tests across responsive layouts.

Accelerated API test cycles by 50% by developing Python-based test harnesses and reusable mock libraries.

Improved cross-browser reliability by decreasing false failures by 33% through custom wait strategies in Selenium scripts.

Increased test feedback loop speed by 60% by integrating headless browser runs in CI with detailed HTML reports.

Reduced onboarding effort for junior QA engineers by creating internal Wiki and reusable template scripts.

Education

Arizona State University
Tempe, AZ, United States of America

Master of Science

Information Technology

Grade: GPA: 4.0

Sri Venkateswara College of Engineering and Technology
Chittoor, India

Bachelor of Technology

Computer Science

Grade: GPA: 3.09

Skills

Programming Languages

Python, Java, JavaScript, SQL, Bash.

Frameworks & Libraries

Spring Boot, Flask, TensorFlow, Selenium, PyTest.

Cloud & DevOps

AWS Lambda, AWS API Gateway, AWS Step Functions, AWS S3, AWS Aurora RDS, AWS SES, AWS EC2, Docker, Jenkins, CI/CD, Git, GitHub Actions.

Databases

PostgreSQL, MySQL, Redis, MongoDB.

Tools & Platforms

Linux, Postman, VS Code, Agile, JIRA.

Technical Concepts

REST APIs, Microservices Architecture, System Design, Fault Tolerance, Unit Testing, Load Balancing.

AI Tools

Cursor, Lovable, Trae, Bolt, Rocket and Emergent.

Projects

Water Potability Predictor and Chatbot App

Summary

Developed a Flask-based Water Potability Predictor and Chatbot App, utilizing TensorFlow, JavaScript, and OpenAI API to provide reliable potability checks and interactive water quality trend analysis.

AI-Powered Feedback Generator

Summary

Developed an AI tool using Flask, OpenAI API, PostgreSQL, AWS Lambda, and SES to automate peer feedback generation and summarize weekly feedback for academic settings.

Validation Using Biometric

Summary

Developed a secure 2FA system using Python, Flask, Kivy, SHA-256, and PyFingerprint, integrating fingerprint-based biometric verification to enhance security and user experience.

IT Asset Management Platform

Summary

Led the development of a microservices-based IT asset tracking platform using Java, Spring Boot, MySQL, and REST APIs, designed to reduce asset misplacement and streamline procurement.