Staff QA Engineer (AI Enabled)

The Ping Identity Data Platform team is building the next generation of enterprise AI governance capabilities to enable secure, scalable, and responsible adoption of AI agents. The team is evolving governance frameworks, platforms, and operational processes to manage AI agents across the enterprise, addressing key areas such as security, compliance, identity, risk management, and responsible AI.

As part of our Data Platform team, you will help define and implement next-generation QA automation and AI-driven testing capabilities across our platform. You will build intelligent test automation frameworks, leverage AI to improve test coverage and accelerate defect detection, and automate validation across APIs, services, workflows, and end-to-end customer scenarios. You will work closely with engineering, product, security, and other cross-functional teams to drive quality from design through delivery, while exploring innovative AI-driven approaches to make our testing more intelligent, scalable, and efficient.

You Will:

• Design, develop, and maintain QA automation frameworks and automated test suites covering Identity Governance capabilities such as certifications, lifecycle management, workflows, and Separation of Duties (SoD), ensuring high-quality and reliable product releases.
• Build and enhance AI-driven test automation capabilities that leverage AI/LLMs to generate test scenarios, expand test coverage, identify potential defects, analyze failures, and accelerate the overall software testing lifecycle.
• Create automated validation for AI agents, tools, MCP servers, workflows, APIs, and enterprise integrations, including functional, integration, regression, performance, security, and end-to-end testing.
• Contribute to rapid prototyping and iteration of AI-powered testing solutions, while learning and adopting evolving AI frameworks, testing tools, agentic technologies, and industry best practices.
• Leverage AI coding assistants and agentic development tools to improve test automation productivity, accelerate test development, generate meaningful test data and scenarios, and improve test coverage while maintaining modularity, maintainability, observability, and code quality.
• Develop intelligent automation for test failure analysis, defect detection, root-cause identification, and regression analysis, reducing manual investigation and improving feedback cycles.
• Collaborate with Engineering, Support, Product, Security, and customer-facing teams to troubleshoot issues, reproduce customer scenarios, identify root causes, and deliver automated regression coverage to prevent recurring issues.
• Develop automated tests to validate AI agent performance, usage, operational health, security, and reliability across supported AI platforms and integrations.
• Contribute to automated logging, metrics, monitoring, and observability validation, ensuring AI agents and governance capabilities meet operational and compliance requirements.
• Explore and evaluate emerging AI testing and agentic automation frameworks, interoperability standards such as MCP and Agent-to-Agent communication, and technologies that can enable autonomous or intelligent QA automation.
• Continuously identify opportunities to replace manual testing with scalable, reliable, and AI-driven automation, improving release confidence, test coverage, execution speed, and overall engineering efficiency.
• Document technical designs, automation frameworks, test strategies, implementation details, operational procedures, and QA engineering best practices.

You Have:

• Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience.
• 8+ years of experience in software engineering, QA automation, test engineering, or a related technical discipline.
• Strong programming experience with JavaScript/TypeScript and/or Java.
• Strong proficiency with Google Cloud, AWS, and other cloud infrastructure technologies, including testing and troubleshooting cloud-based distributed systems.
• Strong experience designing, building, adapting, and maintaining scalable QA automation frameworks and test harnesses using tools such as Jest, Playwright, Cypress, or equivalent technologies.
• Demonstrated ability to rapidly create new test harnesses, adapt existing automation to new architectures and product requirements, and continuously improve test coverage and execution efficiency.
• Strong experience owning test strategy and test inventory, including exploratory testing, functional testing, regression testing, mini-regression testing, end-to-end testing, and release validation.
• Strong ability to analyze failures, establish reproducible test scenarios, collaborate closely with Engineering on root-cause analysis and verification, report test/release status, and drive efficient, high-quality releases.