Job Description

About the Role

We are looking for an experienced Senior QA Automation & AI Testing Engineer to transform our current manual QA process into a modern, automation-first, CI/CD-integrated and AI-assisted quality engineering function.

The successful candidate will be responsible not merely for writing automated test scripts, but for re-engineering the entire testing lifecycle — from requirements analysis and test design through automated execution, defect management, reporting and release quality gates.

Requirements: AI-assisted test design , automated test generation , automated execution , CI/CD , intelligent failure analysis , reporting , release quality gate

The person hired for this role will be expected to design and implement this transformation.

Job Specification

1. QA Process Transformation

- Assess the existing QA/testing process and identify inefficiencies, duplication and gaps.

- Define and implement a modern Quality Engineering / Automation-first QA strategy.

- Establish appropriate testing levels including:

- Unit testing

- API testing

- Integration testing

- UI testing

- Regression testing

- Smoke testing

- Performance testing

- Security testing

- Compatibility testing

- End-to-end testing

- Define what should be automated versus what should remain manual.

- Establish appropriate automation coverage and quality KPIs.

- Introduce risk-based and requirements-based testing rather than simply executing large numbers of test cases.

2. Test Automation Architecture

Design and implement scalable automation frameworks for web, mobile and API-based applications.

Evaluate and select appropriate modern frameworks/tools such as:

- Playwright

- Cypress

- Selenium

- Appium

- REST Assured

- PyTest

- Jest

- Postman/Newman

- Cucumber/BDD where appropriate

The candidate should be capable of selecting the right tool for the problem, rather than being tied to a particular framework.

Responsibilities include:

- Developing reusable automation frameworks.

- Creating Page Object / Screen Object / component-based architectures where appropriate.

- Building reusable test utilities and libraries.

- Managing test data.

- Supporting parallel execution.

- Implementing reliable synchronization and wait strategies.

- Reducing flaky tests.

- Maintaining automation code as part of the software engineering lifecycle.

3. API & Backend Test Automation

Build a strong API/backend testing capability rather than depending primarily on UI automation.

Experience should include:

- REST APIs

- JSON/XML

- Authentication and authorization

- Database validation

- API contract testing

- Integration testing

- Microservices testing

- Message queues/events where applicable

- Mocking and service virtualization

The candidate should understand the principle:

4. CI/CD & Continuous Testing

Integrate automated testing into the development pipeline.

Hands-on experience with tools such as:

- Jenkins

- GitHub Actions

- GitLab CI/CD

- Azure DevOps

- Docker

- Kubernetes where applicable

The candidate should be able to design pipelines such as:





Developer Commit
?
Build
?
Unit Tests
?
API Tests
?
Integration Tests
?
UI Smoke Tests
?
Regression Tests
?
Test Report
?
Quality Gate
?
Deployment

Automated tests should be capable of running:

- On every build/commit where appropriate

- On pull requests

- Nightly

- Before releases

- On-demand

5. AI-Assisted Testing & Testing Agents

This is a critical responsibility of the role.

Evaluate and introduce practical AI-assisted QA and autonomous testing capabilities.

The candidate should understand how modern AI can be applied to:

- Requirement analysis

- Test scenario generation

- Test case generation

- Test data generation

- Test script generation

- Test maintenance

- Failure analysis

- Root-cause analysis

- Defect classification

- Regression test selection

- Self-healing automation

- Natural-language-to-test automation

- Exploratory testing

- Visual validation

- Intelligent test prioritization

The candidate should be capable of evaluating emerging AI testing agents / AI-native testing platforms and determining where they provide genuine productivity gains.

AI should be used to augment QA engineers, not simply generate large volumes of test cases.

6. LLM & Agent Integration

Experience using LLMs such as ChatGPT, Claude, Gemini, GitHub Copilot or equivalent tools for software testing is desirable.

The candidate should understand how to build practical workflows around LLMs, including:

- SRS ? test scenarios

- User story ? acceptance criteria

- Requirements ? test coverage

- Requirements ? automation candidates

- Test case ? automation code

- Failed test ? failure analysis

- Logs ? probable root cause

- Defect ? reproduction steps

- Release ? automated QA summary

Experience with AI agents, MCP-based tooling, APIs, RAG or LLM integration into engineering workflows will be an advantage.

7. Test Management & Quality Engineering

Establish measurable QA processes and dashboards.

Define metrics such as:

- Automation coverage

- Requirements coverage

- Regression coverage

- Defect escape rate

- Defect detection effectiveness

- Test execution time

- Automation execution time

- Flaky test percentage

- Mean time to identify failures

- Mean time to resolve defects

- Production defects

- Release quality

- Automation ROI

The goal should be to measure quality and engineering effectiveness, not simply the number of test cases executed.

8. Test Reporting & Quality Gates

Implement automated reporting using appropriate tools and dashboards.

Reports should clearly identify:

- Passed tests

- Failed tests

- Blocked tests

- New failures

- Recurring failures

- Flaky tests

- Defect correlation





- Regression status

- Build health

- Release readiness

Implement automated quality gates that can prevent deployments when predefined quality thresholds are not met.

9. Framework Governance

Establish standards for:

- Automation coding

- Test naming

- Test data

- Test environments

- Test tagging

- Test categorization

- Logging

- Reporting

- Version control

- Code review

- Framework architecture

- Test maintenance

Create reusable automation assets that can be used across multiple projects.

10. Mentoring & QA Team Development

The successful candidate will act as a technical leader for the QA team.

Responsibilities include:

- Mentoring manual testers.

- Training QA engineers in automation.

- Establishing automation best practices.

- Conducting technical reviews.

- Helping team members transition from test execution to quality engineering.

- Creating internal QA standards and reusable assets.

- Building a culture of automation-first testing.

Other Details

Skill Set

6+ years of software QA/testing experience. Robust understanding of software testing methodologies. Significant hands-on automation experience. Experience designing automation frameworks. Strong programming skills in at least one of: Java Python JavaScript/TypeScript C# Strong API testing experience. Strong web application testing experience. Experience with Selenium, Playwright, Cypress or equivalent. Experience with CI/CD. Hands-on Jenkins/GitHub Actions/GitLab CI or equivalent. Git and source-control experience. SQL/database testing. Experience with Agile/Scrum development. Experience integrating automated tests into build pipelines. Ability to troubleshoot failed automation and identify root causes. Playwright with TypeScript/Python/Java. API automation. Docker. Kubernetes. Cloud environments such as AWS/Azure/GCP. Performance testing. Security testing awareness. Mobile automation using Appium. Test reporting/dashboarding. AI-assisted software testing. LLM-based development/testing workflows. AI testing agents. Self-healing test automation. Visual regression testing. Contract testing. Microservices testing. Test orchestration and parallel execution. Leadership & Problem-Solving Skills The candidate must demonstrate the ability to: Challenge inefficient QA processes. Identify automation opportunities. Decide what not to automate. Design maintainable automation rather than large collections of scripts. Reduce regression testing time significantly. Diagnose flaky automation. Introduce engineering discipline into QA. Evaluate new testing technologies objectively. Balance automation investment against business value. Work closely with developers, DevOps, product managers and architects.

Qualification

Bachelor's or Master's degree in: Computer Science/ Information Technology/ Engineering/ or equivalent technical discipline. Relevant professional experience may substitute for formal education.

Location

Kochi, Infopark Phase 2

Experience

6+ years

Salary

as per industry standards

Job posted date

7/09/2026

📌 Senior QA Automation & AI Testing Engineer (India)
🏢 Armia Systems
📍 India