AI/ML and Quality Engineering expert with over 18 years of experience in the software industry, blending deep expertise in AI/ML, Generative AI, and advanced test automation. Holding an M.Tech in Artificial Intelligence & Machine Learning, with 3+ years dedicated to designing and developing AI/ML and GenAI-powered solutions for intelligent test automation, code generation, and adaptive testing workflows.
Proven track record in leveraging GenAI models (LLMs) to build tools that improve test efficiency, dynamic locator resolution, and self-healing automation frameworks. Experienced in all phases of the SDLC, with 16+ years of hands-on experience in automation, performance, and security testing across enterprise-scale systems. Passionate about integrating AI into QA processes to drive innovation, reduce manual effort, and accelerate delivery.
Experienced in designing and development complex systems and integration with AI Models
SAP HANA DB & Analytics SAP Ariba Retail Tech Stack & Tools
As a senior technologist in AI-driven test automation and quality engineering at SAP, I have played a transformative role in building intelligent testing ecosystems powered by machine learning, generative AI, and DevOps automation. My contributions have significantly enhanced efficiency, reduced defect leakage, and accelerated release cycles for enterprise platforms such as SAP HANA and SAP Ariba Retail.
As Head of Quality – Cloud at Netradyne, I was responsible for overseeing the quality strategy and end-to-end validation of Driver•i—an AI-, Computer Vision–, and IoT-powered fleet safety platform. The system integrated smart in-vehicle devices with a cloud-based analytics engine to monitor real-time driver behavior and provide actionable safety insights.
I architected and led the development of a Cloud Integrated Test Automation Framework (Java + Python) to ensure seamless validation of data ingestion pipelines, cloud analytics, and REST APIs. My responsibilities also included establishing automated performance testing pipelines, executing cloud and edge device validation, and implementing robust security testing using industry-standard tools and practices.
Java, Python, Selenium, REST APIs, PyTest, TestNG, Cucumber, JMeter, Jenkins, AWS (IoT, S3, EC2, SQS, CloudWatch), MongoDB, DynamoDB, Postgres, Node.js, Express, Apache Tomcat, GitHub, Burp Suite, ZAP, Wireshark, Kali Linux, Parrot OS
Overview of Project: Worked in following Projects
1. UHCI (Earlier FrontierMedex): is providing Travel Security Management, Emergency medical and evacuation services to its corporate and individual customers. It includes Transport using ground and Air ambulance support, Emergency medical services etc.
2. UFE(United Front End): UFE is a dedicated application in UHG responsible for routing claims to various Adjudication and payment Engine as well as processing Accumulators and Life Time Maximums to coordinate the benefits between various payers in the USA.
3. 835 HIPPA Compliance : For the health care industry to achieve the potential administrative cost savings With Electronic Data Interchange (EDI), standards have been developed and need to be implemented consistently by all organizations. To facilitate a smooth Transition into the EDI environment, uniform implementation is critical.
Roles and Responsibilities:
Performance Testing
Penetration Testing
Java
Selenium
Python
Jmeter, Locust
TestNG
AngularJS
Spring Boot
Javascript
Nodejs
Linux (Ubuntu/Kali/Parrot)
Groovy
MySQL
MongoDB
BDD, Jasmine, Cucumber
AWS
IoT
AI & ML
Protractor, Testcafe
Generative AI
Agentic AI
AREAS OF EXPERTISE/EXPOSURE
ISTQB
GenAI and LLM Models
AHM250
ISTQB