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Senior AI Driven Test Automation Architect

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Hewlett Packard Enterprise Development LP
Full Time position
Listed on 2026-07-27
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), AI QA / Validation Engineer, Software Testing
Salary/Wage Range or Industry Benchmark: 120000 - 243000 USD Yearly USD 120000.00 243000.00 YEAR
Job Description & How to Apply Below

Senior AI Driven Test Automation Architect

Who We Are

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next.

We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description

This role will own the architecture and evolution of enterprise-scale automation platforms spanning UI, API, integration, resiliency, and cloud-native validation. The ideal candidate has successfully designed and implemented automation platforms supporting large-scale enterprise applications and has demonstrated experience applying AI-powered solutions to software quality engineering challenges. You will partner with engineering, Dev Ops, platform, and AI teams to improve release confidence, reduce validation cycles, and drive predictive quality practices across the SDLC.

Responsibilities
  • Architect and scale enterprise-grade automation frameworks for UI, API, integration, and end-to-end testing using Playwright and Type Script.
  • Design scalable testing platforms integrated with CI/CD pipelines and cloud-native infrastructure.
  • Partner with platform and Dev Ops 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.
Education and Experience Required
  • 8+ years of experience in test automation (API & UI), software quality engineering, or SDET roles with strong architectural ownership
  • 3+ years Playwright and Type Script experience with the ability to design scalable, maintainable automation frameworks from the ground up.
  • 2+ yrs of experience using AI-assisted development tools such as Git Hub Copilot or equivalent coding assistants to accelerate test automation and engineering workflows.
  • Hands-on expertise integrating automated testing into CI/CD platforms such as Git Hub Actions, Git Lab CI, Azure Dev Ops, 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,…
Position Requirements
10+ Years work experience
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