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Performance Test Engineer with 10+ years in Performance Engineering & AI/LLM Enhancements
A competent professional with nearly 17 years of rich experience in Product QA in Performance Testing and Copilot and Performance and Functional Testing working on web applications, Client/Server technologies, and Performance & Regression tests, Exploratory testing, Gatling and database load testing and JMeter, Neo Load, Load Runner, SOAP UI, Blaze meter, REST API, Rest Assured, Salesforce and Neo Load and Gitlab and Jenkins. Performance Engineering: software development lifecycle and architecture, performance testing and validation, capacity planning, application performance management, and problem detection and resolution. Performance Monitoring tools: Dynatrace and Performance Analysis, Workload Modelling, and App Dynamics. Detailed table covering the critical areas in Heap dump and Thread dump analysis using Visual tools. Domains worked on - Gained experience across various domains such as Retail and Investment Banking and WMS [Warehouse Management System , Wealth Management, hospitality, Salesforce, Health Insurance, AI/LLM Enhancements, healthcare, logistics, finance, Insurance, eCommerce, ETL – data warehouse, HRMS, supply chain, and banking. Ensure the testing process integrates seamlessly with the Agile development workflow while fostering team collaboration and delivering a quality product as Scrum master. Facilitate Scrum Ceremonies: Lead daily stand-ups, sprint planning, retrospectives, and review meetings. Conducted load testing on cloud-based environments, including Azure, AWS, Redline13, and Jenkins. Actively managed project activities including test planning, test estimation, resource management, QA monitoring & controlling, test progress reporting, defect management, and Integration. Applied AI-based workload modeling to adjust concurrency, pacing, and data variations dynamically. Leveraged LLM-powered log analyzers to detect root causes of response time degradation and system bottlenecks. Built predictive monitoring dashboards using AI to forecast
SMU
MBA · Project Management
N/A – Present
HIC Global
Performance Architecture and Performance Engineer
October 1, 2025 – Present
India
Espire Info Labs Private Limited
Performance Architecture and Performance Tester
September 1, 2021 – October 1, 2025
Gurgaon, Haryana, India
IndicSoft Technologies Pt. Ltd.
QA Manager for Automation API and Mobile Testing
February 1, 2020 – February 1, 2021
Noida, Uttar Pradesh, India
Mamta Arts and Software Testing
QA Manager for Automation and Mobile Testing
August 1, 2017 – December 1, 2019
Noida, Uttar Pradesh, India
Opera Solutions
Automation Testing and API Performance Testing
August 1, 2010 – July 1, 2017
Noida, Uttar Pradesh, India
Annik Technologies Services Pvt. Ltd
Manual testing
September 1, 2007 – August 1, 2010
Gurgaon, Haryana, India
TPN Connect – Consignment-based company
September 1, 2021 – October 1, 2025
Domain -Supply Chain Management (SCM) and WMS [Warehouse Management System ] WMS is a subdomain of SCM, focusing on warehouse and inventory operations within the larger supply chain process. Cullina is a TPN Connect client and handles daily consignment creation for over 80,000 transactions. Working on JMeter, Neo Load - Integration and Gatling and Performance Testing, and API testing functional testing. and micro-services. Applied AI-based workload modelling to adjust concurrency, pacing, and data variations dynamically. Leveraged LLM-powered log analysers to detect root causes of response time degradation and system bottlenecks. Built predictive monitoring dashboards using AI to forecast CPU, memory, and network utilisation trends. Designed AI recommendation engines for post-run analysis, suggesting infra tuning, caching, and DB optimisations. Generating a HAR File to upload the script recorded and GitLab. Running Load test in Azure Cloud Load Test and Azure Monitoring, both client and server side. Neoload: Performance testing with Neoload for the logistics domain. Database Optimization and Query Tuning - Jmeter Load testing. Use AppDynamics to monitor the performance metrics. Performance testing with API testing used the Swagger API of Cullina, used in Tosca, Tosca TestCase Export. Tosca ExecutionList Export. Worked on the collection of TestCases (ExecutionEntries) to be executed.
CEVA Logistics domain
September 1, 2021 – October 1, 2025
Conducted API testing using JMeter, Neo Load, and Tosca with various user roles, ranging from admin to standard users. The project was subsequently transitioned to Jenkins for automation. Applied AI-based workload modelling to adjust concurrency, pacing, and data variations dynamically. Leveraged LLM-powered log analysers to detect root causes of response time degradation and system bottlenecks. Built predictive monitoring dashboards using AI to forecast CPU, memory, and network utilisation trends. Designed AI recommendation engines for post-run analysis, suggesting infra tuning, caching, and DB optimisations. Generating HAR File to upload the script recorded and GitLab. Database Optimization and Query Tuning as a Jmeter Load testing. Neoload: Performance testing with Neoload for the logistics domain. Use AppDynamics to monitor the performance metrics. Salesforce: Performance testing with Jmeter and Tosca, used Salesforce *, tce and *.tcs - Tosca TestCase Export. Used Salesforce Tosca ExecutionList Export. Worked on the collection of TestCases (ExecutionEntries) to be executed.
Rebound - B2B Retail/E-Commerce domain
September 1, 2021 – October 1, 2025
Retail Domain → because it’s product sales and purchases. E-Commerce Domain → if it’s done via an online platform. B2B (Business-to-Business) sub-domain → since the transactions are between companies, not individual consumers. Rebound is a UK-based electronic product-selling company. Working on JMeter, Neo Load, Tosca, and SOAP UI – Performance load testing and API testing. Testing of Microservices API Running behind the application. Applied AI-based workload modeling to adjust concurrency, pacing, and data variations dynamically. Leveraged LLM-powered log analyzers to detect root causes of response time degradation and system bottlenecks. Built predictive monitoring dashboards using AI to forecast CPU, memory, and network utilization trends. Designed AI recommendation engines for post-run analysis, suggesting infra tuning, caching, and DB optimizations. Used BlazeMeter for HAR File and GitLab. Running Load test in Azure Cloud Load Test and Azure Monitoring, both client and server side. Neoload and JMeter: Performance testing with Neoload for the logistics domain. Database Optimization and Query Tuning - Jmeter Load testing. Use AppDynamics to monitor the performance metrics. Performance testing with API testing utilised the Swagger API of Rebound using Tosca and Tosca TestCase Export. Tosca ExecutionList Export. Worked on the collection of TestCases (ExecutionEntries) to be executed.
Tribepad HRMS Domain
September 1, 2021 – October 1, 2025
Tribepad is a cloud-based Applicant Tracking System (ATS) and recruitment management platform widely used by HR departments to streamline talent acquisition, recruitment, and onboarding processes. Tribe Pad is a job consulting project that involves domain-specific industry processes. I worked on JMeter, LoadRunner, and Tosca for API testing as part of the project. Applied AI-based workload modeling to adjust concurrency, pacing, and data variations dynamically. Leveraged LLM-powered log analyzers to detect root causes of response time degradation and system bottlenecks. Built predictive monitoring dashboards using AI to forecast CPU, memory, and network utilization trends. Designed AI recommendation engines for post-run analysis, suggesting infra tuning, caching, and DB optimizations. Used BlazeMeter for HAR File and GitLab. Running Load test in Azure Cloud Load Test and Azure Monitoring, both client and server side. Load Runner and JMeter upload the HAR File and GitLab. Database Optimization and Query Tuning - Jmeter Load testing.
Rebound - BOM [ Bill of Materials]
September 1, 2021 – October 1, 2025
Rebound is a UK-based electronic product-selling company. Working on JMeter, Neo Load, and Performance load testing and API testing with Tosca. Chrome Browser: Used Blazemeter for AD Login by-pass. Blazemeter is a plugin extension of the Chrome browser to bypass the OTP on mobile. Neoload and JMeter: Performance testing with Neoload for the logistics domain. Use AppDynamics to monitor the performance metrics.
Banking app – Rural and Cooperative bank
January 1, 2021 – December 31, 2023
Features of Rural and Cooperative Banks that are especially useful for small-scale industry (SSI) employees. These banks are designed to support local businesses, farmers, and small Industries with accessible financial services. Rural and Cooperative banks give affordable loans, savings products, financial inclusion, and access to government schemes. Project description: Credit & Loan Support | Savings & Deposits | Financial Inclusion | Government Scheme Linkages | Support for Local Development | Technology & Modern Services (Growing Trend) | Profit-Sharing (in Cooperative Banks) | Microfinance & SHG Linkages | Local Language & Accessibility | Social Security & Insurance Products | Emergency & Seasonal Credit | Employment Generation Support | Relationship-based Banking | Lower Transaction Costs. Working on JMeter, Load Runner, and SOAP UI – Performance load testing and API testing. Testing of Microservices API Running behind the application. Use AppDynamics to monitor the performance metrics. Performance testing for Database testing utilised DB Query to optimise the Reader Room production database in Tosca, specifically through Tosca TestCase Export. Tosca ExecutionList Export. Worked on the collection of TestCases (ExecutionEntries) to be executed.
SBM - Swachh Bharat Mission (Web and Mobile App)
February 1, 2020 – February 1, 2021
Generating HAR File to upload the script recorded. Testing Tools: on JMeter, SOAP UI, and Blazemeter. A framework that includes high-level and low-level design, load balancing, caching, and database testing. Role: QA Manager and Testing Designer. Database Optimization and Query Tuning - Jmeter Load testing. Description: Responsible for validating APK files and native apps. Responsibilities: Understand system requirements, Prepare and execute test cases, Conduct functional, regression, integration, and usability testing, Track issues and report them using bug tracking tools, Prepare bug matrices. Non-Functional Testing: JMeter, and applied all methodologies as a Subject Matter Expert for non-functional testing. Software Tools Used: Jmeter, SOAP UI, Blazemeter, Jenkins, TestLink, and JIRA.
Matrix Mobile
August 1, 2017 – December 1, 2019
Non-Functional Testing: on JMeter, Integration, and Gatling, and applied all methodologies as a Subject Matter Expert for non- functional testing. Generate HAR File upload the script recorded. Database Optimization and Query Tuning - Jmeter Load testing. Testing Tool Used: JMeter, SOAP UI, Blazemeter, Jenkins, TestLink, JIRA, and Manual Testing.
BIQ and QlikView
December 1, 2013 – July 1, 2017
Worked on BIQ – own company – Opera Solutions product ETL tool. Push the ETL data in QlikView. Verify the data on the dimension display on the QlikView dashboard. Verify and run the SQL data query in JMeter. Application Performance Monitoring (APM) - Dynatrace.
Amex SIP - Spend Intelligent Platform
May 1, 2012 – November 1, 2013
Senior QA Engineer. Client: Amex – Ameriprise.
HMA SOP - Staffing Optimisation
April 1, 2012 – August 1, 2012
Product Testing for Health Management Associates. Application Performance Monitoring (APM) - Datadog.
HMA Dashboard
January 1, 2012 – April 1, 2012
Senior QA Engineer. Client: HMA – Health Management Associate.
Hotel Marcos - Hospitality Domain
May 1, 2011 – November 1, 2013
Testing API and UI load testing. Application Performance Monitoring (APM) - Dynatrace.
BankingMSB - Investment Banking & Capital Markets Domain- Wealth Management and Investment domain
March 1, 2011 – December 1, 2011
Client: MSSB – MORGAN STANLEY SMITH BARNEY, USA. Application Performance Monitoring (APM) - Dynatrace. Non-Functional Testing: JMeter and applied all methodologies as a Subject Matter Expert for non-functional testing. Testing Tool Used: on JMeter Integration and SOAP UI, Blazemeter, Jenkins, TestLink, JIRA and Manual Testing.
FAP – Financial Advisers Performance Tool
March 1, 2011 – December 1, 2011
Senior QA Engineer. Client: MSSB – MORGAN STANLEY SMITH BARNEY, USA. Application Performance Monitoring (APM) – Datadog.
PM –TOOL
December 1, 2007 – July 1, 2008
Manual and data testing. Project Lead.
Project Status Project Tracking Tool
October 1, 2007 – March 1, 2008
Manual and data testing. Project Lead.
MSDOC - EDC and MIO
September 1, 2007 – February 1, 2008
Manual and data testing. Project Lead.
AZ 104 Professional Azure Administrator
Unknown
June 1, 2026 – Present
ISTQB Certified Tester
ISTQB (International Software Testing Qualifications Board)
June 1, 2026 – Present
Professional Scrum master certified
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience across various domains (Retail, Banking, Logistics, HRMS, etc.) and their involvement in diverse projects suggest a high degree of adaptability and a broad understanding of different business contexts. Their Scrum Master certification and experience in leading QA teams indicate a collaborative mindset and a fit for Agile environments. The continuous mention of AI/LLM enhancements in their recent roles also points to a proactive approach to adopting new technologies, which is a positive cultural indicator for innovation-driven teams. The candidate's long tenure in the industry and leadership roles suggest stability and a commitment to quality.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and communication skills through their QA Manager and Project Lead roles, successfully managing teams of over 10 members and facilitating Scrum ceremonies. Their experience in client interaction, requirements mapping, and test strategy creation indicates a proactive and collaborative operational fit. The emphasis on AI/LLM integration in performance testing suggests an adaptability to modern methodologies and a forward-thinking approach.