Indexnine Technologies - Quality Assurance Automation Lead

Role : QA Automation Lead - AI-Enabled Quality Engineering

Experience : 8 to 13 Years

Location : Pune

Role Overview :

We are looking for a Senior QA Tech Lead to drive end-to-end quality engineering, build scalable automation frameworks, and lead QA teams in delivering high-quality software in agile product environments. This role requires strong expertise in test strategy, automation architecture, agile delivery, and AI-enabled testing practices. You will work closely with engineering, product, and client stakeholders to ensure quality is built into the product from design to release. As part of our evolving engineering landscape, this role will also progressively involve leveraging AI for quality engineering, including writing agents, developing scripts, analyzing code quality (e.g., Sonar), and validating AI-generated outputs. A strong engineering foundation and hands-on coding capability are essential to succeed in this role.

Key Responsibilities :

Quality Engineering & Test Strategy :

- Define test strategy, scope, and risk-based testing approaches aligned with product requirements.

- Ensure effective implementation of STLC across all development phases.

- Lead functional, integration, and regression testing for product releases.

- Maintain test cases, test metrics, and release quality reports including execution summaries and defect insights.

- Track and govern key delivery quality metrics such as Defect Leakage, Automation Coverage, and Regression Coverage to ensure release quality and delivery efficiency.

- Establish quality gates, release readiness criteria, and continuous improvement practices.

Test Automation :

- Design and implement scalable automation frameworks aligned with product architecture.

- Develop and maintain automation test suites integrated with CI/CD pipelines.

- Conduct automation code reviews and enforce automation best practices and standards.

- Drive automation coverage improvements across functional, API, UI and regression testing layers.

Product & Engineering Collaboration :

- Participate in requirement and design discussions to ensure early quality validation.

- Contribute to MVP scoping, backlog prioritization, and product roadmap discussions.

- Identify opportunities to build reusable testing utilities and quality accelerators.

Agile Delivery & Project Leadership :

- Translate requirements into clear test scenarios and acceptance criteria.

- Lead sprint planning, backlog refinement, and testing execution.

- Track delivery progress, proactively identify risks, and communicate status to stakeholders.

- Monitor sprint quality metrics, defect trends, and release health dashboards.

Team Leadership & Mentorship :

- Lead QA teams with clear ownership, accountability, and delivery alignment.

- Mentor engineers in automation practices, test design, debugging techniques, and engineering fundamentals.

- Promote a culture of quality, collaboration, and continuous improvement.

AI-Enabled Testing & Engineering :

- Leverage AI tools to accelerate test design, automation development, and defect analysis.

- Evaluate and adopt AI-assisted testing tools and productivity platforms.

- Develop scripts, workflows, and AI agents to improve testing efficiency and coverage.

- Analyze code quality issues (e.g., Sonar reports) and ensure quality gates are met.

- Define testing approaches for AI-driven systems and validate AI-generated code outputs.

Required Skills :

- Strong expertise in software testing, test strategy, and quality engineering practices.

- Hands-on experience designing automation frameworks and CI/CD integrated testing.

- Solid computer science fundamentals (data structures, algorithms, system design basics).

- Strong programming skills with hands-on coding experience (e.g., Java, Python, JavaScript, or similar).

- Experience with test management and defect tracking tools (JIRA, Zephyr, Azure DevOps, etc.).

- Strong understanding of Agile delivery models and sprint execution.

- Proven experience leading QA teams and collaborating with product and engineering stakeholders.

- Strong understanding of delivery quality metrics including Defect Leakage, Automation Coverage, and Regression Coverage.

- Exposure to AI-assisted testing, code analysis tools (e.g., Sonar), or modern developer productivity tools is preferred.

Preferred Technology Stack :

- Automation Tools : Selenium, Playwright, Cypress, Appium, Rest Assured

- Programming Languages : Python, Robot, JavaScript, TypeScript

- API Testing : Postman, REST Assured, SOAP UI

- CI/CD Tools : Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps

- Test Management & Defect Tracking : JIRA, Zephyr, TestRail, Azure DevOps

- Performance Testing : JMeter, LoadRunner

- Code Quality & Security : SonarQube, Checkmarx

- Cloud & DevOps Exposure : AWS, Azure, Docker, Kubernetes

- Version Control : Git, Bitbucket

- AI Productivity & Testing Tools : GitHub Copilot, ChatGPT, AI-assisted testing platforms

(ref:hirist.tech)