AI Test Automation Technical Architect

Job Description

The AI Test Automation Technical Architect is responsible for designing and implementing intelligent, scalable, and future-proof test automation frameworks that leverage AI/ML capabilities to quickly test our AI powered Xvantage platform. This role bridges traditional automation architecture with AI-driven testing strategies, ensuring faster releases, improved coverage, and predictive quality analytics.

Key Responsibilities

·       Must have proven capabilities to drive Touchless automation using AI in all phases of STLC (Test Data, Test planning, Test Execution, Analysis, Run, Maintenance and Quality analysis)

·       Architect AI-driven test automation frameworks for web, mobile, API, microservices and enterprise applications.

·       Integrate AI-powered tools for self-healing scripts, intelligent test generation, and anomaly detection.

·       Define end-to-end automation strategy, including functional, performance, security, and accessibility testing.

·       Implement MLOps for testing: model-based test prioritization, defect prediction, and risk-based testing.

·       Ensure CI/CD integration with automated quality gates and real-time dashboards.

·       Collaborate with development, QA, and DevOps teams to align automation with delivery pipelines.

·       Evaluate emerging AI testing technologies and recommend adoption strategies.

·       Mentor teams on AI-assisted automation practices and framework design.

·       Optimize test execution performance and reduce maintenance through AI-based self-healing.

·       Establish governance and best practices for automation and AI ethics in testing.

Role Description

This role requires a blend of technical depth and strategic vision:

·       Acts as the technical authority for automation architecture and AI integration.

·       Drives innovation in testing by introducing predictive analytics and autonomous testing.

·       Ensures scalability, maintainability, and resilience of automation frameworks.

·       Works closely with product owners, architects, and QA leads to define quality KPIs and automation roadmaps.

Core Competencies

Technical Expertise

·       Strong programming skills: Java, Python, JavaScript.

·       Deep knowledge of test automation frameworks (Selenium, Playwright, Cypress, Appium).

·       Experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face).

·       Familiarity with AI testing tools (Testim, Mabl, Applitools, ACCELQ).

·       Proficiency in API testing (RestAssured, Postman) and performance tools (JMeter, Gatling).

·       CI/CD tools: Jenkins, GitHub Actions, Azure DevOps.

·       Cloud platforms: AWS, Azure, GCP.

AI & Data Skills

·       Understanding of ML model lifecycle and data pipelines.

·       Knowledge of predictive analytics for defect detection.

·       Experience with self-healing locators and intelligent test prioritization.

Architectural Thinking

·       Ability to design modular, reusable, and scalable frameworks.

·       Expertise in microservices testing strategies.

·       Knowledge of containerization and orchestration (Docker, Kubernetes).

Leadership & Collaboration

·       Strong communication and stakeholder management.

·       Ability to mentor teams and drive adoption of AI-based testing.

·       Strategic mindset for quality engineering transformation.

Soft Skills

·       Analytical thinking and problem-solving.

·       Adaptability to emerging technologies.

·       Strong documentation and governance skills.

Ideal Candidate Profile

·       Education: Bachelor’s/Master’s in Computer Science or related field.

·       Experience: 10+ years in QA/automation architecture, 3+ years in architecture, expert  to AI/ML.

·       Certifications: ISTQB Advanced, AI/ML certifications (AWS AI, TensorFlow Developer), DevOps certifications.