QA Engineer - AI Native

Summary

Storyteller is a high-growth B2B SaaS platform that enables companies to add Stories experiences to their own apps and websites. The QA Engineer role focuses on using AI to enhance software quality through automated testing and collaboration with product owners and builders throughout the engineering lifecycle.

Responsibilities

• Use AI coding agents and related tools to explore the SDK codebases, understand behaviour and accelerate quality work
• Use product, technical, integration and release risk to identify the highest-value quality improvements
• Design, build and maintain useful unit and component tests for SDK behaviour
• Design, build and maintain integration tests covering SDK interaction with Storyteller services and APIs
• Put automated tests into active CI and release workflows, with failures that are clear and actionable
• Prove that tests detect meaningful breakage rather than merely producing passing output
• Investigate bugs using code, logs, APIs, test results and product behaviour
• Where appropriate, follow a well-understood issue through to a bounded production fix
• Work with builders to improve testability and prevent repeated classes of defects
• Turn repeated investigation or testing work into reusable AI workflows, tools, checks or test assets
• Communicate clearly in Slack and other team systems: state the evidence, impact, current understanding, owner and next action
• Contribute useful AI-assisted engineering practices to the wider SDK team while remaining primarily accountable for quality outcomes
• Contribute to tvOS, Android TV, Fire TV, Web and Roku as the role's scope expands

Skills

• AI-native execution – You use AI to do substantive technical work, not only to write or summarise. You can give an agent useful context, break down an ambiguous problem, inspect its work, redirect it when necessary and keep going when the first approach fails
• Quality and validation judgment – You can decide what is worth testing, recognise superficial tests and demonstrate that an automated test provides real protection. You think about false confidence, false positives, brittle tests, maintainability and failure diagnosis
• Agency and ownership – You can take an ambiguous quality risk, investigate it, gather evidence, choose a sensible next step and move the work towards a useful outcome
• Technical comfort – You are comfortable working with repositories, code, APIs, CI, logs, command-line tools and automated test frameworks. You can understand and challenge AI-generated code well enough to validate and land it safely
• Problem solving and systems thinking – You distinguish symptoms from root causes. When a problem repeats, you look for a reusable test, tool, check or workflow instead of treating every occurrence as a new manual task
• Clear communication – You communicate concisely and directly. You make evidence, impact, uncertainty, ownership and next actions visible without requiring someone else to reconstruct the situation
• Learning velocity – You are curious and can become effective in unfamiliar products, codebases and tools quickly. You change your approach when the evidence shows that it is not working
• Experience with mobile applications or SDKs
• Experience with Swift or Kotlin
• Experience with API integration
• Experience with automated testing or test frameworks

Qualifications

Must Haves

• AI-native execution – You use AI to do substantive technical work, not only to write or summarise. You can give an agent useful context, break down an ambiguous problem, inspect its work, redirect it when necessary and keep going when the first approach fails
• Quality and validation judgment – You can decide what is worth testing, recognise superficial tests and demonstrate that an automated test provides real protection. You think about false confidence, false positives, brittle tests, maintainability and failure diagnosis
• Agency and ownership – You can take an ambiguous quality risk, investigate it, gather evidence, choose a sensible next step and move the work towards a useful outcome
• Technical comfort – You are comfortable working with repositories, code, APIs, CI, logs, command-line tools and automated test frameworks. You can understand and challenge AI-generated code well enough to validate and land it safely
• Problem solving and systems thinking – You distinguish symptoms from root causes. When a problem repeats, you look for a reusable test, tool, check or workflow instead of treating every occurrence as a new manual task
• Clear communication – You communicate concisely and directly. You make evidence, impact, uncertainty, ownership and next actions visible without requiring someone else to reconstruct the situation
• Learning velocity – You are curious and can become effective in unfamiliar products, codebases and tools quickly. You change your approach when the evidence shows that it is not working

Nice to Haves

• Experience with mobile applications or SDKs
• Experience with Swift or Kotlin
• Experience with API integration
• Experience with automated testing or test frameworks