Codex Expert- AI
About The Position
The Codex Expert- AI designs and develops Codex-driven testing and automation frameworks for first-party applications across the P2P landscape. The role builds reusable AI automation skills, prompts, workflows, agents, utilities, and framework components that application teams can apply consistently, and establishes a scalable foundation for UI, API, integration, regression, and end-to-end testing. The position uses Python and modern testing frameworks, applies AI-assisted development to accelerate test and code workflows, and integrates automated testing into CI/CD pipelines. It focuses on reusable libraries, standards, framework architecture, reliability, and guardrails for AI-generated code and test assets. The role collaborates with development, QA, architecture, product, and DevOps teams, provides technical guidance, and maintains documentation. The position is listed as hybrid in SFO, CA, with flexible work-from-home options available.
Responsibilities
- Design and develop Codex-driven testing and automation frameworks for first-party applications.
- Build reusable AI automation skills, prompts, workflows, agents, utilities, and framework components for application teams.
- Establish a scalable automation foundation covering UI, API, integration, regression, and end-to-end testing.
- Develop automation solutions using Python and testing frameworks such as Playwright, Selenium, and PyTest.
- Apply AI-assisted development techniques to test-case generation, test-script creation, code generation and refactoring, test-data generation, failure analysis and debugging, and automation maintenance.
- Create reusable libraries, patterns, templates, and standards rather than application-specific one-off automation.
- Integrate automated testing into CI/CD pipelines, including Jenkins, GitHub Actions, Azure DevOps, or similar platforms.
- Develop API automation for REST-based services using appropriate testing libraries and frameworks.
- Define framework architecture, coding standards, reusable modules, logging, reporting, configuration management, and exception-handling patterns.
- Improve automation reliability by addressing flaky tests, execution failures, synchronization issues, and environment dependencies.
- Build validation and guardrail mechanisms around AI-generated code and test assets.
- Collaborate with developers, QA engineers, architects, product teams, and DevOps teams to identify high-value automation opportunities.
- Conduct code reviews and provide technical guidance on AI-driven automation engineering practices.
- Maintain technical documentation covering automation architecture, reusable skills, framework standards, and implementation guidelines.
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What This Job Offers
Job Type
Full-time
Education Level
No Education Listed
