Shape and refine the operational model for AI-driven test automation programs
Customize and expand a universal rule and skill framework across varied client setups
Guide executive-level stakeholders on quality strategy, software lifecycle enhancements, automation evolution, and AI integration
Lead efforts to standardize test frameworks while accommodating project-specific needs
Evaluate AI-generated artifacts such as code, architectural choices, reports, rules, and test assets
Detect systemic flaws, false alarms, contract violations, redundant logic, or inefficient implementations rapidly
Trace problems to root causes and implement corrective measures at appropriate system levels
Enhance the consistency and quality of engineering workflows assisted by AI
Establish guidelines and boundaries for responsible and effective AI use in test automation
Collaborate with AI coding agents and structured prompting techniques to streamline development workflows
Continuously refine prompts, skills, layered rules, and integrations with core frameworks
Optimize token consumption and cost efficiency without compromising delivery standards
Lead the development and evolution of a scalable Playwright and TypeScript-based automation framework
Design and manage page objects, reusable UI components, fixtures, selectors, reporting systems, and test data handling
Enforce high standards in test design and architectural coherence
Ensure the framework remains portable and scalable across multiple client engagements

Competitive market rate

Flexible, project-dependent

Distributed engineering teams collaborating on client delivery

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
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
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
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

Available based on project and location

Sigma Software is hiring a Principal AI-Augmented Test Automation Engineer