AZ-204 Certified Associate Software Engineer with 1.5+ years of experience building and supporting Azure cloud-native services, including Azure Health Data Services (FHIR). Experienced in developing and validating REST APIs, automating deployments and operational workflows, and troubleshooting production issues involving authentication, authorization, and Azure configurations. Skilled in Azure DevOps CI/CD, Infrastructure as Code using Bicep/ARM Templates, and Python automation for reporting and deployment validation. Also contributed to security and compliance activities (Microsoft Secure 360) and performed end-to-end API testing using tools like Insomnia to ensure reliable releases for enterprise healthcare platforms.…

Mahesh Kopparthi

AZ-204 Certified Associate Software Engineer with 1.5+ years of experience building and supporting Azure cloud-native services, including Azure Health Data Services (FHIR). Experienced in developing and validating REST APIs, automating deployments and operational workflows, and troubleshooting production issues involving authentication, authorization, and Azure configurations. Skilled in Azure DevOps CI/CD, Infrastructure as Code using Bicep/ARM Templates, and Python automation for reporting and deployment validation. Also contributed to security and compliance activities (Microsoft Secure 360) and performed end-to-end API testing using tools like Insomnia to ensure reliable releases for enterprise healthcare platforms.…

Available to hire

AZ-204 Certified Associate Software Engineer with 1.5+ years of experience building and supporting Azure cloud-native services, including Azure Health Data Services (FHIR). Experienced in developing and validating REST APIs, automating deployments and operational workflows, and troubleshooting production issues involving authentication, authorization, and Azure configurations.

Skilled in Azure DevOps CI/CD, Infrastructure as Code using Bicep/ARM Templates, and Python automation for reporting and deployment validation. Also contributed to security and compliance activities (Microsoft Secure 360) and performed end-to-end API testing using tools like Insomnia to ensure reliable releases for enterprise healthcare platforms.

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Skills

Experience Level

Azure
Expert
API
Expert
Python
Expert
GitHub
Expert
PowerShell
Expert
SQL
Expert

Language

English
Fluent
Telugu
Fluent

Work Experience

Associate Software Engineer at WaferWire Cloud Technologies, Hyderabad, India
February 1, 2025 - Present
Developed and maintained Azure FHIR REST APIs for Microsoft Health & Life Sciences (HLS) platform, enabling secure healthcare data exchange using HL7 FHIR. Automated infrastructure provisioning and deployments using Bicep/ARM Templates, PowerShell, and Azure DevOps CI/CD pipelines to improve consistency and reduce manual effort. Built Python automation to streamline operational workflows, reporting, and deployment validation. Investigated and resolved production issues spanning authentication/authorization, REST APIs, and Azure resource configurations as part of live site support. Contributed to Microsoft Secure 360 by monitoring vulnerabilities, validating remediation, tracking pipeline health, and supporting security compliance. Performed end-to-end REST API testing using Insomnia and collaborated with cross-functional teams using Azure monitoring/diagnostic tools and logs to improve reliability and document solutions.

Education

Master of Computer Applications (MCA) at KGRL College of PG Education, Bhimavaram
January 1, 2022 - January 1, 2024
Bachelor of Science in Computer Science (BSc) at B V Raju Institute of Computer Education, Bhimavaram
January 1, 2019 - January 1, 2022

Qualifications

Microsoft Certified: Azure Developer Associate (AZ-204)
January 11, 2030 - August 7, 2026

Industry Experience

Healthcare, Life Sciences, Software & Internet
    Cyberbullying Prevention on Social Media Using AI & Machine Learning

    Developed an intelligent web-based application to help detect and prevent cyberbullying across social media platforms using Machine Learning and Natural Language Processing (NLP).
    Key Features
    Detects abusive, offensive, and bullying messages in real time.
    Uses NLP techniques for text preprocessing and sentiment analysis.
    Classifies messages into bullying and non-bullying categories using machine learning models.
    Provides instant alerts and moderation support.
    User-friendly web interface for message analysis.
    Secure backend with database integration for storing predictions and reports.
    Technologies Used
    Python
    Machine Learning
    Natural Language Processing (NLP)
    Flask/FastAPI
    HTML
    CSS
    JavaScript
    SQLite/MySQL
    Git
    Outcome Built a scalable solution that assists users and moderators in identifying harmful online content, promoting a safer and healthier social media environment.

    Cyberbullying Prevention on Social Media Using AI & Machine Learning

    Developed an intelligent web-based application to help detect and prevent cyberbullying across social media platforms using Machine Learning and Natural Language Processing (NLP).

    Key Features
    Detects abusive, offensive, and bullying messages in real time.
    Uses NLP techniques for text preprocessing and sentiment analysis.
    Classifies messages into bullying and non-bullying categories using machine learning models.
    Provides instant alerts and moderation support.
    User-friendly web interface for message analysis.
    Secure backend with database integration for storing predictions and reports.

    Technologies Used
    Python
    Machine Learning
    Natural Language Processing (NLP)
    Flask/FastAPI
    HTML
    CSS
    JavaScript
    SQLite/MySQL
    Git

    Outcome Built a scalable solution that assists users and moderators in identifying harmful online content, promoting a safer and healthier social media environment.