We are looking for a AI Enabled Quality Automation Lead to drive end-to-end testing strategy, build scalable automation frameworks, and lead QA teams responsible for delivering reliable software products.
This role is designed for an experienced quality automation professional with strong foundations in automation architecture, software testing practices, coding, and agile product delivery.
You will work closely with engineering teams, product teams, and customer stakeholders to integrate quality across the complete software development lifecycle. The role requires technical depth, hands-on automation experience, and the ability to guide teams in solving complex quality challenges.
At Indexnine, we are building an AI-first engineering culture where quality engineering goes beyond traditional testing. You will use AI tools, automation, and engineering practices to accelerate test creation, improve coverage, analyze software quality, and validate modern AI-enabled applications.
Quality Engineering & Test Strategy
-
Define testing strategy, scope, quality standards, and risk-based testing approaches aligned with product objectives.
-
Establish strong quality practices across all phases of the software development lifecycle.
-
Lead functional testing, integration testing, regression testing, and release validation activities.
-
Maintain test documentation, quality metrics, execution reports, and defect analysis insights.
-
Monitor engineering quality indicators including defect leakage, automation coverage, regression coverage, and release readiness.
-
Establish quality gates and continuous improvement practices to improve software reliability.
Test Automation
-
Design and build scalable automation frameworks aligned with application architecture and engineering practices.
-
Develop and maintain automation suites integrated with CI/CD workflows.
-
Review automation code and establish engineering standards for test development.
-
Improve automation coverage across UI, API, functional, and regression testing layers.
-
Build reusable automation components, testing utilities, and quality accelerators.
Product & Engineering Collaboration
-
Participate in requirement analysis, architecture discussions, and design reviews to identify quality considerations early.
-
Collaborate with product teams during MVP planning, backlog prioritization, and roadmap discussions.
-
Work with engineering teams to improve testability, maintainability, and overall product quality.
-
Identify opportunities to improve engineering efficiency through automation and AI-enabled solutions.
Agile Delivery & Project Leadership
-
Convert product requirements into clear test scenarios, acceptance criteria, and validation plans.
-
Lead testing activities across sprint planning, backlog refinement, execution, and releases.
-
Track delivery progress, identify risks early, and communicate quality status to stakeholders.
-
Monitor sprint health, defect trends, testing effectiveness, and release quality metrics.
Team Leadership & Mentorship
-
Lead QA teams with ownership across planning, execution, and delivery outcomes.
-
Mentor engineers on automation practices, test design, debugging approaches, and engineering fundamentals.
-
Build a team culture focused on accountability, technical growth, collaboration, and continuous improvement.
AI-Enabled Testing & Engineering
-
Apply AI tools to accelerate test design, automation development, defect analysis, and engineering productivity.
-
Evaluate and adopt AI-assisted testing platforms and developer productivity tools.
-
Build scripts, workflows, and AI agents to improve testing efficiency and coverage.
-
Analyze code quality reports using tools such as SonarQube and drive quality improvements.
-
Define validation approaches for AI-enabled systems and review AI-generated code outputs.
