AI DevOps & Platform QA Engineer

About the Role

Join PwC Acceleration Center India as an AI DevOps & Platform QA Engineer – Senior Associate. You will play a pivotal role in enhancing the quality and reliability of software and product innovations within our Managed Services network. Focus on testing and quality assurance to meet rigorous client standards. Leverage problem-solving skills and critical thinking to navigate complex challenges and build client relationships. Opportunity to mentor junior team members. Work closely with multidisciplinary teams within our Cloud Engineering, Data & Analytics network, analyzing complex concepts and developing innovative solutions.

Key Responsibilities

• Conducting automation testing and quality control to validate software reliability
• Collaborating with teams to implement agile product management and program methodologies
• Utilizing AI fluency and AI-human collaboration to enhance testing processes
• Performing defect management and debugging to identify and resolve software issues
• Developing and managing test cases and environments to support software testing life cycle
• Applying analytical thinking and problem diagnosis to improve software quality assurance
• Executing performance testing and reliability validation to confirm system functionality
• Leading acceptance testing and documentation testing to support client requirements
• Engaging in system troubleshooting and fault analysis to optimize software performance
• Promoting quality assurance best practices and process management within projects

Requirements & Tech Stack

• At least a Bachelor's degree
• Oral and written proficiency in English required

Qualifications

• Demonstrating proficiency in Agile SDLC and Agile Program Management
• Utilizing Automation Testing and Quality Assurance Best Practices
• Excelling in Software Quality Assurance (SQA) and Quality Control Testing
• Managing Test Environment Management (TEM) effectively
• Conducting Performance Testing and Reliability Validation
• Analyzing complex data models and debugging efficiently
• Embracing AI-Human Collaboration and AI Fluency in projects