Senior Quality Engineering Specialist – AI

Overview

Senior Quality Engineering Specialist – AI to identify, design, and implement AI-powered solutions across the software engineering lifecycle, enabling automation, accelerating delivery, and improving engineering efficiency.

What you'll do

• Identify opportunities to leverage AI across engineering workflows and software delivery processes
• Design, develop, and implement AI-driven solutions to improve engineering productivity and efficiency
• Build AI agents, copilots, and reusable workflows for software engineering use cases
• Apply AI across the software engineering lifecycle, including requirement analysis, scenario generation, code generation, automation development, data generation, impact analysis, and defect analysis
• Develop and maintain automation frameworks or performance engineering assets based on area of specialization
• Collaborate with Product, Development, Platform, QA, and Engineering teams to drive AI adoption
• Evaluate emerging AI technologies, tools, and frameworks, and recommend practical enterprise solutions
• Integrate AI capabilities into existing engineering processes, CI/CD pipelines, and DevOps workflows
• Analyze engineering challenges and recommend automation and AI-based improvements
• Support implementation, testing, rollout, and continuous improvement of AI solutions
• Provide engineering insights through AI-driven analytics, reporting, and productivity metrics

What you'll need

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
• 7-10 years of experience in Software Engineering, Quality Engineering, Automation, or Performance Engineering
• UI Automation: Selenium, Playwright, Cypress, or similar frameworks using Java/JavaScript
• Performance Engineering: JMeter, LoadRunner, Gatling, or similar tools
• Hands-on experience applying AI across the Software Development Lifecycle (SDLC)
• Experience building AI agents, workflows, copilots, or AI-enabled engineering solutions
• Knowledge of requirements analysis, test scenario generation, code generation, defect analysis, and engineering automation using AI
• Understanding of Large Language Models (LLMs), Generative AI, Prompt Engineering, and AI-assisted development tools

Nice to have

• Experience with AI platforms such as Azure OpenAI, OpenAI, GitHub Copilot, Microsoft Copilot, LangChain, or similar technologies
• Experience developing AI-powered engineering productivity solutions
• Knowledge of Agentic AI frameworks and multi-agent workflows
• Experience integrating AI solutions with engineering tools and platforms
• Familiarity with cloud platforms such as Azure, AWS, or Google Cloud Platform

Details

• Full-time, Hybrid - Bengaluru
• Sedentary work that involves sitting or remaining stationary most of the time, with occasional need to move around the office to attend meetings
• Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor