Full Description

CES has 26+ years of experience in delivering Software Product Development, Quality Engineering, and Digital Transformation Consulting Services to Global SMEs & Large Enterprises. CES has been delivering services to some of the leading Fortune 500 Companies including Automotive, AgTech, Bio Science, EdTech, FinTech, Manufacturing, Online Retailers, and Investment Banks. These are long-term relationships of more than 10 years and are nurtured by not only our commitment to timely delivery of quality services but also due to our investments and innovations in their technology roadmap. As an organization, we are in an exponential growth phase with a consistent focus on continuous improvement, process-oriented culture, and a true partnership mindset with our customers. We are looking for the right qualified and committed individuals to play an exceptional role as well as to support our accelerated growth.

You can learn more about us at: http://www.cesltd.com/

Job Role

• We are looking for a Functional QA Engineer with an AI-First mindset and Business Analyst-level expertise to validate and verify requirements from the earliest stages. This role emphasizes an AI-first approach to functional testing, ensuring quality is built in from requirements through delivery.

In this role, you will apply both your QA expertise and an understanding of emerging AI tools (like intelligent test generation, predictive defect detection, and automated test documentation) to optimize the testing lifecycle.

Key Responsibilities

• Adopt AI-Driven Testing Workflows
• Use AI-powered tools and copilots to design, execute, and optimize functional test cases, improving coverage and reducing repetitive effort.
• Intelligent Test Design & Generation
• Leverage LLM-based tools (e.g., ChatGPT, Testim, Mabl, or similar) to automatically generate and maintain functional test scenarios from user stories, requirements, or code changes.
• Test Execution & Automation
• Execute both manual and automated functional tests; use AI to detect redundant or flaky tests, and to suggest automation candidates.
• AI-Assisted Defect Analysis
• Use AI tools to analyze defect patterns, identify root causes faster, and recommend preventive actions or fixes.
• Test Data Management
• Employ AI tools to generate realistic, synthetic test data while preserving privacy and edge-case coverage.
• Continuous Improvement & Documentation
• Use AI copilots to document test results, generate reports, and maintain test scripts with minimal manual effort.
• Collaboration & Reporting
• Work closely with Product, Dev, and DevOps teams to integrate AI-driven insights into sprint cycles; present QA metrics enhanced by AI analytics.