Senior AI Driven Test Automation Architect

About the role

This role is a Hybrid position requiring 2 days per week at an HPE office.

Responsibilities

• Architect and scale enterprise-grade automation frameworks for UI, API, integration, and end-to-end testing using Playwright and TypeScript.
• Design scalable testing platforms integrated with CI/CD pipelines and cloud-native infrastructure.
• Partner with platform and DevOps teams to provision scalable test environments using Kubernetes and Docker.
• Drive shift-left quality practices by embedding automated quality gates early in the software development lifecycle.
• Build observability-driven testing ecosystems with actionable reporting, diagnostics, and telemetry insights.
• Lead the adoption of AI-assisted quality engineering practices including: AI-generated test creation, Autonomous test maintenance, Intelligent flaky-test analysis, and Defect prediction and root-cause insights.
• Evaluate and integrate LLM-powered testing solutions, AI agents, and GenAI developer productivity tools.
• Define standards for automation architecture, framework governance, coding practices, and reusable testing libraries.
• Mentor engineers and quality teams on modern automation design patterns and AI-enabled testing workflows.
• Collaborate with engineering leadership to establish organization-wide quality engineering strategy and KPIs.
• Contribute to architecture reviews, technical documentation, ADRs, and engineering best practices.

Requirements

• 8+ years of experience in test automation (API & UI), software quality engineering, or SDET roles with strong architectural ownership.
• 3+ years Playwright and TypeScript experience with the ability to design scalable, maintainable automation frameworks from the ground up.
• 2+ years of experience using AI-assisted development tools such as GitHub Copilot or equivalent coding assistants to accelerate test automation and engineering workflows.
• Hands-on expertise integrating automated testing into CI/CD platforms such as GitHub Actions, GitLab CI, Azure DevOps, Jenkins or equivalent platforms where AI is used to optimize or augment validation workflows and determine release readiness.
• Expertise with containerization and orchestration technologies including Docker and Kubernetes.
• Experience and knowledge of cloud platforms such as AWS, Azure, or GCP for automating the provisioning, configuration, and management of scalable test environments.
• Practical experience implementing AI-driven test case generation, including using LLMs to convert requirements/user stories into structured test scenarios and automation scripts.
• Experience using AI-assisted debugging and failure analysis workflows to improve test reliability and reduce flaky tests.
• Experience integrating AI/ML capabilities or AI agents into testing and quality engineering workflows.
• Strong written and verbal communication skills capable of creating technical documentation, architectural guidance, communicating with engineers, architects, and senior leadership.
• Bachelor's or Master’s degree in computer science, Information Systems, or equivalent.

Qualifications

• Exposure to enterprise networking, cloud, or distributed system environments where AI is applied to testing complex systems.
• Experience in Networking or Security Domain.