Software Product Reliability Engineer (AQA) - UniFi Fabric Platform

Location: Taipei

Department: 400-Research and Development

Role Summary

We are looking for a Product Reliability Engineer (AQA) - UniFi Fabric Platform to evolve QA beyond traditional Dev support into customer-driven product reliability ownership.

This role focuses on scalable validation systems and production-like, real-world customer workflow coverage for UniFi Fabric across Identity (Admins and Users), MSP, Zero Trust, provisioning, orchestration, cloud services, client workflows, and application backends. You will work closely with Support, Product, Engineering, Cloud, Identity, client, and application backend teams to translate real customer pain points into repeatable validation coverage and release confidence.

The ideal candidate is a strong SDET / AQA who can build reliable automation systems, debug complex product behavior across frontend, backend, cloud, and client surfaces, and reduce customer risk before issues reach production.

What You’ll Do

• Build and maintain scalable automated validation systems for UniFi Fabric workflows across client, cloud backend, and application backend surfaces.
• Translate Support cases, customer feedback, field issues, and regression patterns into repeatable test scenarios.
• Maintain production-like and real-world workflow environments that reflect customer deployments, data, permissions, upgrades, provisioning, and failure recovery paths.
• Validate dependencies across UniFi Fabric Identity (Admins and Users), MSP, Zero Trust, provisioning, orchestration, admin workflows, permissions, cloud services, clients, and application backends.
• Design end-to-end coverage for login, SSO, RBAC, provisioning, permissions, upgrades, MSP workflows, client-backend integration, and recovery scenarios.
• Partner directly with Support, Product, Dev, Cloud, Identity, client, application backend, and DevOps teams to close the product delivery feedback loop.
• Improve test reliability, observability, debugging, reporting, and release confidence.
• Use AI development tools such as Codex, Claude Code, Cursor, or equivalent tools to accelerate test creation, log analysis, scenario generation, debugging, and automation maintenance.

What We’re Looking For

• 3+ years of experience in SDET, AQA, software testing, test automation, or product reliability engineering.
• Strong hands-on automation experience using Python, TypeScript, Go, Java, or similar languages.
• Experience building API, integration, end-to-end, regression, and system-level automation for cloud, backend, and client workflows.
• Ability to understand customer issues and convert them into clear, repeatable, production-like validation scenarios.
• Strong debugging skills across logs, APIs, databases, cloud services, client apps, application backends, devices, and distributed systems.
• Familiarity with CI/CD, test pipelines, monitoring, observability, and release validation.
• Strong ownership mindset: able to identify quality gaps, define validation strategy, and drive issues to closure.
• Good communication skills and ability to work directly with Support, Product, Engineering, and cross-functional teams.
• Proficiency with AI-assisted engineering workflows, including AI-based test generation, log analysis, spec-driven validation, and automation refactoring.

Preferred Qualifications

• Experience validating connected hardware-software systems across cloud, client applications, application backends, devices, and real-world network environments.
• Familiarity with UniFi Fabric, UniFi OS, IAM, OAuth2, OIDC, SSO, RBAC, permissions, audit logs, Zero Trust, provisioning, orchestration, or admin workflows.
• Experience with production-like test environments, test data management, staging sites, device farms, or real-world workflow validation.
• Experience with Playwright, Cypress, Selenium, Postman, k6, pytest, Robot Framework, or similar tools.
• Experience with AWS, Docker, Kubernetes, message queues, RDBMS / NoSQL, or distributed system testing.
• Experience working directly with Support or customer-facing teams to analyze field issues.
• Interest in agentic engineering and using AI tools to improve automation productivity, reliability, and coverage.

Key Evaluation Criteria

The best candidate should demonstrate:

1. Customer-driven reliability mindset — stays close to real customer pain points and validates production-like workflows, not only Jira tickets from Dev.
2. Automation depth — can build scalable, maintainable, trustworthy validation systems.
3. Product reliability ownership — understands risk across product, cloud backend, application backend, client, identity, permissions, devices, and workflow dependencies.
4. Debugging ability — can isolate root causes across complex distributed systems.
5. AI-native reliability workflow — uses AI tools to increase test coverage, speed, and insight without sacrificing judgment.