Principal AI-Augmented Test Automation Engineer

Job Description

Process & Solution Establishment

• Define and evolve the engagement model for AI-native test automation initiatives
• Adapt and extend the universal rule and skill system for different client environments
• Advise senior stakeholders on quality strategy, SDLC improvements, automation maturity, and AI adoption
• Drive framework standardization while balancing project-specific requirements

Analytical Review & AI Output Validation

• Review AI-generated outputs, including code, architecture decisions, reports, rules, and testing artifacts
• Quickly identify systemic issues, false positives, broken contracts, redundant logic, or inefficient implementations
• Trace issues to their root causes and define corrective actions at the right system layer
• Improve the reliability and quality of AI-assisted engineering workflows

AI-Augmented Testing Operations

• Define principles and guardrails for effective AI usage in test automation
• Work with AI coding agents and structured prompting approaches to optimize engineering workflows
• Continuously improve prompts, skills, layered rules, and framework integrations
• Optimize token usage and cost efficiency while maintaining delivery quality

Test Automation Architecture

• Own and evolve a scalable Playwright + TypeScript automation framework
• Design and maintain page objects, reusable page-element components, fixtures, selectors, reporting, and test data management
• Establish and enforce strong test-design standards and architectural consistency
• Support portability and scalability of the framework across multiple engagements

Qualifications

• Strong hands-on experience with Playwright and TypeScript test automation architecture
• Proven experience building and evolving automation frameworks from scratch
• Deep understanding of scalable E2E testing design patterns and framework organization
• Experience working with AI coding agents such as Cursor, Claude Code, or similar tools
• Strong analytical skills with the ability to validate and challenge AI-generated outputs
• Experience defining methodologies, playbooks, standards, or reusable engineering practices
• Excellent communication and stakeholder management skills
• Ability to work in customer-facing advisory and consulting environments
• Upper-Intermediate level of English 

WILL BE A PLUS:

• Experience building AI-native QA or engineering workflows
• Knowledge of token optimization and AI operational economics
• Experience leading or scaling QA/automation practices
• Understanding of SDLC transformation and quality engineering strategy
• Experience working in consulting or multi-client delivery environments