

Dynamic and results-driven Engineering Manager with 13+ years of experience leading large-scale software testing, automation, and quality engineering initiatives. Proven success in building high-performing teams, driving Agile and AI-driven transformation, and implementing intelligent automation frameworks that leverage machine learning and predictive analytics to enhance delivery speed, scalability, and reliability. Adept at aligning engineering and AI practices with business goals, optimizing CI/CD pipelines using data-driven insights, and managing cross-functional collaboration across global delivery centers. Experienced in integrating AI-powered quality assurance, anomaly detection, and test optimization solutions to accelerate innovation and improve system resilience.
• Spearheaded automation strategy and test process improvement across multiple Agile projects.
• Designed automation solutions integrating AWS Lambda and Python for cloud-based testing.
• Drove deployment transition across DEV, QA, UAT, and PROD ensuring stability.
• Established continuous delivery practices with GitHub/GitLab repositories.
• Conducted technical training to enhance coding standards and team productivity.
Key Impact: Reduced regression cycle time by 35% and delivered SaaS projects with zero
post-release defects.
• Developed and maintained Selenium WebDriver scripts using TestNG, Maven, and Java for
banking and financial projects.
• Automated functional, regression, and smoke testing processes.
• Integrated hybrid frameworks and reusable test components.
• Used ALM/Bugzilla/JIRA for complete defect lifecycle management.
Automation & QA Tools:
Selenium, TestNG, JUnit, Postman, Bruno, Playwright, Cypress, Appium, Bugzilla, TestSigma (AI-based automation), Mabl (self-healing tests), Testimio, Katalon Studio
Programming & AI Frameworks:
Java, Python, SQL, OOPs, FastAPI, LangChain, TensorFlow, PyTorch, OpenAI API, Hugging Face Transformers, Scikit-learn, Pandas, NumPy
AI & Machine Learning in QA:
Generative AI for test case generation (GitHub Copilot, ChatGPT API), Predictive defect analytics, AI-driven anomaly detection, Intelligent test prioritization, Natural Language Test Automation (NLTA), AI-based visual testing (Applitools Eyes, Percy)
Cloud & DevOps / MLOps:
AWS (Lambda, CloudWatch, S3, SageMaker), Jenkins, Bamboo, Maven, Docker, Kubernetes, GitHub Actions, GitLab CI, Azure DevOps, MLflow, Kubeflow, CI/CD Automation Pipelines
Databases & Data Engineering:
MySQL, SQL Server, Redis, MongoDB, PostgreSQL, BigQuery, DataBricks
Testing Types:
Functional, Regression, API, System Integration, GUI, Smoke, Performance, Security, AI Model Testing, A/B Testing, Explainable AI (XAI) validation
Methodologies & Frameworks:
Agile (Scrum, Kanban), Hybrid Automation Frameworks, BDD (Cucumber), TDD, Continuous Testing, AI-Enhanced Agile Delivery
Project Management & Collaboration Tools:
JIRA, Confluence, Asana, Trello, Eclipse IDE, IntelliJ IDEA, VS Code, Notion AI
Soft Skills:
Leadership, Communication, Stakeholder Management, Strategic Planning, Process Improvement, AI Transformation Leadership, Innovation Mindset