Practitioner and architect with over two decades of experience across Quality Engineering, Automation, and Performance at scale. Focused on designing AI-augmented QA ecosystems that enable engineering teams to move from manual validation toward autonomous, intelligence-driven quality systems. Experienced in modernizing complex quality lifecycles by blending classical engineering discipline with emerging AI capabilities to improve reliability, speed, and decision-making across large, distributed platforms.
I am a Technology Program Manager and expert in High-Scale Automation & Performance Testing with over two decades of professional excellence. Currently at Innodata Inc., I specialize in architecting AI-driven QA systems that redefine how enterprises handle quality, combining deep engineering roots at GlobalLogic and Schneider Electric with cutting-edge AI orchestration.
I hold an MBA in Operations & IT from IMT Ghaziabad and a B.Tech in Information Technology. My professional journey has evolved from core testing workflows to designing intelligent systems that leverage LLMs, RAG, and AI-driven health analytics to reduce risk early and drive engineering excellence.
Orchestrating AI-native Quality Engineering strategies and leading large-scale technology programs. Implementing RAG-based systems and intelligent automation for enterprise delivery excellence. Specialized in TestOps and high-scale delivery.
Led high-impact QA transformations for global clients including AgilityPR and Blackboard. Designed Hybrid Automation Frameworks and managed full-scale Performance Engineering lifecycles using industrial-grade testing suites.
Led enterprise-level QA initiatives for CITI Bank (Loan Path) and CEB. Expertly orchestrated LoadRunner and JMeter performance testing alongside cross-platform hybrid automation for complex fintech ecosystems.
Foundational focus on SAP-based regression testing, complex enterprise configuration management, and core industrial application quality assurance.
A deep dive into the AI-Driven QA Ecosystem: A comprehensive suite for Next-Gen Automation, High-Scale Performance, and Intelligent Quality Assurance.
Designed to solve the bottleneck of manual test case creation and maintainability, this workspace leverages RAG (Retrieval-Augmented Generation) and Vision LLMs to deliver an 80% reduction in QE effort while ensuring 100% traceability.
Aggregates Jira, Confluence, and Phabricator data into Vector DBs.
LangChain & GPT-4o processing for requirement-to-test mapping.
Self-healing Playwright scripts and AIO Tests API integration.
Interactive Streamlit RCA Dashboards and Failures Clustering.
Live overview of sprint progress, defect leakage, and core quality metrics across all active streams.
AI-driven Root Cause Analysis providing deep insights into recurring failures and system bottlenecks.
Autonomous agent that sifts through logs and traces to pinpoint the exact line of failure in complex systems.
Automatically crafts exhaustive test cases from requirements, ensuring 100% path coverage for new features.
Next-gen agent that writes production-ready Playwright/Cypress scripts directly from manual test descriptions.
AI-driven code review for automation engineers, ensuring test suites are robust, efficient, and maintainable.
Autonomous REST/GraphQL tester that explores endpoints, validates schemas, and hunts for vulnerabilities.
Predictive engine that analyzes past defects to identify high-risk areas where bugs are most likely to escape.
Intelligent bridge that converts failed test run data into comprehensive, high-quality Jira tickets automatically.
Collaborative space for engineering leads to track team velocity, quality trends, and ROI of automation.
Deep-time quality data storage and analysis, revealing long-term trends and effectiveness of QA shifts.
Real-time pulse of your automation infrastructure, identifying flaky environments and unstable pipelines.
The centralized control room for all running test suites, providing live updates on execution rates.
A collection of custom-built tools and resources for learning, growth, and efficiency
Deep dives into Quality Engineering, AI-native automation, and DevOps architectures.
Capturing moments beyond code - exploring cultures, landscapes, and experiences.
Interested in collaborating on AI-native quality systems or just want to say hi? I'm always open to discussing new opportunities and innovation.