About Me
Software Engineer with experience in developing test automation infrastructure using Selenium Grid and integrating CI/CD pipelines. Proficient in containerization with Docker and Azure DevOps to streamline deployment processes.
Experienced in implementing GxP-compliant software development life cycle (SDLC) processes and developing end-to-end test automation suits for web, desktop, and API applications.
Skilled in creating automation scripts for data processing using PowerShell and Python. Certified in Azure DevOps, Scrum methodologies, and committed to best practices in software development.
$ ls ./skills
// Technical stack and expertise
Work Experience
xLM Continuous Validation - Jacksonville, FL (2021-2025)
Lead Software Engineer - AI
Nov 2023 – Jul 2025Architected AI test automation platform with RAG workflows, reducing manual effort by 90% while leading cross-functional team of 5 engineers.
Key Achievements
- Led cross-functional team delivering cIV AI Platform with RAG & prompt-engineering workflows, cutting manual test-authoring by 90% (21 CFR Part 11 compliant)
- Designed GPU-accelerated inference with PyTorch/vLLM on AWS/Azure with robust evaluation loops
- Instrumented Git/GitHub CI/CD pipelines and automated release governance with standardized SOPs
- Orchestrated Kubernetes/Selenium Grid device-farm for parallel experimentation
- Led SQL Server to cloud migration with extensive PowerShell automation
Technologies
SDET II
Sep 2022 – Oct 2023Built enterprise automation frameworks reducing deployment cycles by 40%, led xLMCore NuGet development through 15+ versions.
Key Achievements
- Designed end-to-end automation frameworks with Selenium/Playwright/SpecFlow, cutting deployment cycles by 40%
- Led xLMCore NuGet package development (v0.0.1 to v2.0.15) for GxP test automation
- Integrated test suites into CI/CD pipelines with Azure DevOps and Docker
- Developed Jira/Azure DevOps integration eliminating duplicate reporting
- Conducted comprehensive API testing ensuring data integrity and system reliability
Technologies
SDET I
Jul 2021 – Aug 2022Automated enterprise application validation ensuring 21 CFR Part 11 compliance, deployed real-time Power BI dashboards for test visibility.
Key Achievements
- Performed UAT and API testing with SpecFlow ensuring 21 CFR Part 11 compliance
- Automated validation for enterprise apps (Veeva, Sage, Rhythm) using Selenium/Appium/WinAppDriver
- Established end-to-end reporting pipeline with automated data ingestion
- Deployed live Power BI dashboards for real-time test execution visibility
Technologies
Education
Master of Science in Data Science
Worcester Polytechnic Institute, Worcester, MA
Program Overview
Currently pursuing advanced graduate studies in Data Science with focus on machine learning, statistical modeling, and data engineering. The program emphasizes practical application of cutting-edge AI/ML techniques and large-scale data processing.
Academic Excellence:
Achieved perfect 4.00 GPA in first semester
coursework, demonstrating strong foundation in advanced data
science concepts and methodologies.
Areas of Focus
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Advanced Machine Learning: Deep learning architectures, neural networks, and AI model optimization
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Statistical Modeling: Bayesian inference, time series forecasting, and predictive analytics
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Big Data Engineering: Distributed computing, data pipelines, and scalable analytics infrastructure
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Applied Research: Real-world data science projects and industry collaboration
Bachelor of Science in Applied Statistics & Analytics
NMIMS University, Mumbai, India
Program Overview
- Completed an intensive 151-credit program (3-year curriculum comparable to 120-130 American credits / 302 ECTS credits)
- Core Focus: Statistics, Data Analysis, Programming, and Applied Mathematics
- Developed proficiency in R, Python, and C programming languages
- Engaged in multiple research projects applying statistical concepts to real-world scenarios
Key Skills Developed
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Statistical Analysis: Hypothesis testing, regression analysis, experimental design, and data-driven decision making
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Data Science: Machine learning algorithms, predictive modeling, data visualization, and pattern recognition
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Programming: Algorithm development, data structures, software engineering practices in R and Python
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Applied Analytics: Integrated statistics with economics, finance, and computer science
Notable Courses
Data Science
Time Series Analysis
Financial Risk Modeling
Multivariate Statistics
Projects
AI-Powered Web Navigation Agent
FeaturedAn intelligent agent that autonomously navigates web applications for testing and validation purposes. Built with state-of-the-art LLM technologies to improve efficiency and reduce manual testing efforts.
Key Responsibilities
- Managed end-to-end product development from concept to implementation, including agent coding
- Created system architecture and led a cross-functional team through agile sprints
- Integrated LLM technologies to improve web application testing efficiency
GxP-Compliant Agile Development Service
A comprehensive service built on Atlassian Jira to enable GxP-compliant Agile sprint development, balancing regulatory requirements with Agile methodologies.
- Developed a comprehensive service on Atlassian Jira for GxP-based Agile sprint development
- Ensured compliance with regulatory requirements while maintaining Agile principles
Sentiment-Based Trading System
An innovative intraday trading system leveraging news sentiment analysis and technical indicators to make informed trading decisions, achieving impressive returns.
- Built an intraday trading system based on news sentiment analysis and technical indicators
- Adapted BERT model for financial sentiment classification, achieving ~2.6% average daily return
Wikipedia Content Extractor
A Python utility that efficiently extracts and organizes content from Wikipedia pages, outputting structured JSON data for further use in applications or research.
- Wrote a Python script to extract and organize Wikipedia content
- Created JSON output with URLs and associated content
Certifications
Professional certifications that validate my expertise in cloud computing, agile methodologies, and software development best practices.
Azure DevOps - AZ-900
Microsoft
Gained foundational knowledge of Azure services, cloud concepts, and core Azure DevOps principles, which enhanced my ability to manage CI/CD pipelines and cloud resources effectively.
Certified Scrum Developer
Scrum Alliance
Acquired practical skills in Agile methodologies, Scrum practices, and teamwork, enabling me to contribute effectively to agile development teams and deliver high-quality software iteratively.
Software Development Processes
Coursera
Enhanced understanding of various software development lifecycles, best practices, and methodologies, enabling me to optimize project workflows and improve code quality through structured processes.
Certification Journey
My certification journey reflects my commitment to continuous learning and professional growth in the fields of software development, cloud computing, and agile methodologies. Each certification has helped me enhance my skills and deliver more value in my professional roles.
Key Learnings
- Modern cloud architecture and services deployment on Azure
- Agile and Scrum methodologies for team collaboration and efficient software delivery
- Software development lifecycle optimization and best practices
Certification Timeline
Azure DevOps
2024Scrum Developer
2022SDLC Processes
2021Future Certification Goals
I'm constantly looking to expand my knowledge and skills. My next certification goals include advanced Azure certifications, AI/ML specializations, and deepening my expertise in modern software architecture.
Blog
Thoughts, tutorials, and insights on software development
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My Bookshelf
Books that shaped my thinking and career
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