Pravin Patke

Experienced Principal SDET Engineer with 9.4+ years of expertise in designing and automating scalable software, implementing robust CI/CD pipelines, and leading high-performing engineering teams. Proven track record of delivering high-quality, resilient testing solutions across Linux, web-based applications, storage, cloud, AI/ML, multimedia, and embedded domains. Advanced proficiency in Python, Pytest, Selenium, Playwright, Kubernetes, Terraform, AWS, Ansible, and Infrastructure as Code (IaC).

Developed LLM-based test case generation using ChatGPT and Claude to improve test coverage and identify edge-case scenarios. Designed prompt engineering strategies to generate optimized automation scripts and validate complex workflows. Built AI-driven defect prediction models using historical test data to proactively identify high risk areas.

Developed AI-assisted self-healing automation frameworks to dynamically handle locator changes and reduce script failures.

Project Lead – QA (Freelance) - PRP Softwares

(2023-12 - 2026-04)

• Conducted functional testing of web-based applications using Selenium.
• Written scripts for Gen AI and Agentic AI applications using Playwright, Selenium, Python and Pytest.
• Improved automation scripts for LLM models using Python libraries.
• Directed cross-functional team of 9 engineers to deliver robust end-to-end test automation, CI/CD pipelines, and cloud infrastructure.
• Executed concurrent execution solutions using Go, Python and C++.
• Applied ML concepts (supervised/unsupervised learning, NLP) to analyze defect patterns and improves test strategy.
• Integrated LLM pipelines and AI agents for test data generation, validation, and reporting

QA Lead - Quick Heal Technologies

(2023-04 - 2023-07)

• Guided a team of 7 members to the design and development of an end-to-end desktop application automation framework for Quick Heal's security suite.
• Automated critical functional, regression, smoke tests for desktop app using Playwright and Selenium with Python and Pytest and improving test efficiency and coverage.
• Created and Integrated UI automation scripts with Jenkins CI/CD pipelines, enabling scheduled execution and immediate reporting of results.
• Applied ML concepts (supervised/unsupervised learning, NLP) to analyze defect patterns and improve test strategy.
• Leveraged AI tools (OpenAI API and Vertex AI) for intelligent test execution and optimization.

Principal SDET Engineer - Persistent Systems

(2022-10 - 2023-03)

• Improved and maintained Ansible playbooks to automate the deployment, configuration, and performance benchmarking of MySQL, SQL, and Hadoop data platforms.
• Integrated AI-driven automation pipelines into CI/CD platforms, including Jenkins and GitHub Actions, enabling continuous intelligent testing.
• Enabled parallel and distributed test execution using Kubernetes and Docker, improving overall test execution efficiency.
• Built end-to-end, AI-driven testing workflows combining UI automation (Playwright and Selenium), API testing, and database validation.
• Systematized test case prioritization using AI models, reducing regression cycle time.
• Developed scalable UI automation frameworks using Selenium, Playwright, Python, and Pytest.
• Validated storage architectures and ETL pipelines, improving data reliability by 30% and maintaining 99.9% system availability.
• Collaborated with cross-functional teams to identify and resolve 15+ performance bottlenecks, reducing response times by 25%.
• Defined an enterprise-level, AI-driven QA strategy aligned with DevOps practices and business objectives.
• Established automation framework standards, reusable components, and governance models to enable scalable and maintainable test automation.

Principal Software Development Engineer in Test - Calsoft

(2022-02 - 2022-10)

• Mentored a team of 7 engineers, driving test planning, test case design, and end-to-end automation for new features and platform enhancements.
• Stabilized and enhanced the automation framework using Python, Shell scripting, Pytest, and Ansible, integrating it with Jenkins for continuous testing and deployment.
• Performed REST API testing and load testing using Python Requests and Locust.
• Containerized test and staging environments using Docker and orchestrated them with Kubernetes, improving scalability and reproducibility.
• Implemented the Page Object Model (POM) framework using Selenium and Python for maintainable UI automation.
• Automated web-based UI functionality using Selenium, Playwright, Python, and Pytest.

Senior Software Development Engineer in Test, Scrum Master - Veritas Technologies

(2018-01 - 2022-02)

• Wrote Shell/ Python scripts for validation of storage component's functionality.
• Validated complex storage stacks — including file systems, disk groups, VERITAS Volume Manager, VCS, CVM, Cluster File System, and VERITAS Volume Replicator (VVR) — across versions 5.x, 6.x, and 7.x.
• Performed scale-in and scale-out storage testing using add node, delete node functionality.
• Written automation scripts for file and volume replication workflows for disaster recovery, ensuring backup and recovery readiness in critical failure scenarios.
• Improved test coverage by 40–60% using AI-assisted automation
• Reduced regression execution time by 50–70% through intelligent test prioritization
• Enhanced UI automation scripts using Selenium, Playwright with Python and Pytest, increasing test automation coverage by 40% and reducing regression testing time by 50%.
• Develop Storage products build automation tests using C++ and CMake files.
• Fine-Tuned containerized cluster test environments using Docker and Kubernetes.
• Wrote complex MySQL queries.

Software Test Engineer - Imagination Technologies

(2016-06 - 2018-01)

• Performed build generation using Makefiles and CMake files
• Executed robust regression test suites on CSIM and Linux builds, measuring and analyzing system performance metrics.
• Generated vx_testbench device drivers for video encoder and decoder on Linux platform.
• Written test cases for Video Decoder codec's and tested on FPGA Grid's early silicon.
• Verified image classification, accuracy, precision, recall, F1-Score metrics across multi-core embedded platforms, including GPU and SoC's.
• Evaluated Tridymite/Helix/Quartz cores for video codec cores by creating device drivers.
• Wrote python scripts for Device driver features automation for Linux platform.

Ph.D - AI/ML - LPU, Jalandhar, India (2024)

M.Tech - Data Science - BITS Pilani, Pilani, India (2020)

DAC - Advance Computing - CDAC Acts, Pune, India (2015)

B.Tech - CSE - SGGSIET, Nanded, India (2013)