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.
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:
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:
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:
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.
