Consultant

Senior QA Engineer, End-to-End Test Automation (GenAI & ACCELQ) Key responsibilities: Strong knowledge of cloud platforms (AWS, Azure, GCP) including deployment and management of applications Familiarity with Generative AI concepts, specifically large language models (LLMs), and their application in real-world projects using Accello Hands-on experience with Deep Learning, LLM and Python Ability to think creatively and collaborate about applying AI to solve business problems with multiple capabilities, including Experience Design, Change Management and Process Reengineering Sound Knowledge of Software engineering design patterns and practices. Strong understanding of Functional programming, basic data structures and algorithms. Strong problem solving, analytical and interpersonal skills. Experience architecting and developing AI or machine learning solutions on platforms such as AWS, Databricks, Azure, Google Cloud and OpenAI. Strategize and architect: Define and implement the end-to-end test automation strategy, using ACCELQs Gen AI capabilities and autopilot features to accelerate the QA lifecycle. Generate test assets: Utilize ACCELQs natural-language processing (NLP) to automatically generate comprehensive test cases, test data, and modular test logic from user stories and business requirements Automate E2E workflows: Develop robust, scalable automation scripts that validate complex business processes across multiple platforms, including web, API, and mobile. Oversee autonomous testing: Manage the continuous integration and execution of ACCELQs autonomous tests, including those for visual regression and self-healing, within CI/CD pipelines. Enhance and maintain: Leverage AI-powered analytics and insights to continuously optimize test suites, reduce maintenance overhead, and increase test stability and reliability. Collaborate and coach: Work closely with product, development, and manual QA teams to empower citizen testers. Act as a subject matter expert on AI-driven test automation and mentor junior team members. Integrate tools: Ensure seamless integration of ACCELQ with other tools in the development ecosystem, such as Jira, Jenkins, GitHub, and Slack. 1-3 years years of software engineering experience in Python 1-3 years of experience in Django, Flask and other python frameworks 5+ years of hands-on experience in software quality assurance and test automation. 2+ years of demonstrable experience with AI-powered test automation platforms, with a focu.