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AI Augmented QA Engineer

Open 17d

Summary

Builds and maintains AI-orchestrated testing frameworks and automated tooling to accelerate quality assurance across engineering teams, using Python, Playwright, and AI tools like Cursor and Claude.

AI Augmented QA Engineer

Location: Auckland, Hybrid Department: Engineering | Role Type: Shared Service / Force Multiplier
Fixed Term Role - ASAP to 28th May 2027


THE MISSION

The AI-Augmented QA Engineer builds and owns our quality infastructure. Unlike traditional QA roles, you don't sit inside a single pod to manually click through features; you serve as a force multiplier across all pods. Your mission is to build the automated frameworks and AI-orchestrated tooling that allow Product Engineers to verify their own work with confidence.


This is a "Quality-as-Code" role. In an environment moving at AI-augmented speeds, you are responsible for building the safety nets that catch characteristic AI failures—hallucinated logic, shallow error handling, and compliance gaps—before they ever reach production. You don't gatekeep delivery; you accelerate it by making high-quality shipping the path of least resistance.


WHAT YOU WILL DO


  • Infrastructure Design: Build and maintain AI-orchestrated frameworks (Python/Playwright) that are modular and usable by every pod.
  • AI-Generated Strategy: Use AI tools (Cursor, Claude, and others) to transform feature specs into comprehensive test plans, specifically hunting for obscure edge cases and failure scenarios.
  • Hands-On Testing: Perform manual and exploratory testing where automated coverage doesn’t yet exist. Know where the risks are in the product surface and prioritise accordingly.
  • Stress & Scale: Build load-testing infrastructure to simulate high-throughput scenarios across our translation APIs and verification pipelines.
  • AI Code Verification: Identify where AI-generated code introduces security gaps or hallucinated compliance behaviour, and build automated detection into the shared quality layer.
  • Shared Asset Library: Develop a central repository of test assets that pods can extend and reuse, preventing "reinventing the wheel" across the organization.




WHAT WE ARE LOOKING FOR


AI-Augmented Testing

  • AI as a daily tool: You already use AI in your workflow – coding assistants, test generation, prompt engineering. Not curious about AI; already doing it.
  • The Irony of AI: You understand that AI can generate tests that pass without actually covering failure modes. You have the intuition to catch these "false positives."
  • Automated Generation: Experience using AI to generate test plans, edge case scenarios, and automation scripts, coupled with the technical depth to verify their validity.


Technical Foundation

  • Testing Fundamentals: You understand test strategy, test design, coverage and risk – not just how to write a test script.
  • Python Proficiency: You can write and maintain test automation, scripts and frameworks in Python.
  • Tooling: Experience with test automation frameworks (Playwright, Selenium, or similar) and CI/CD pipeline integration.
  • Failure Pattern Recognition: Knowledge of where AI-generated code commonly stumbles: security boundaries, data validation, and overconfident logic.


Mindset

  • Self Directed: You figure things out, ask good questions, and don’t wait for someone to hand you a process
  • Cross-Team Fluency: This role is shared across engineering pods with different contexts and cadences. You manage that without being managed.
  • Prevention over Detection: You don’t just find bugs; you design systems that prevent them from being written in the first place.
  • Speed + Rigor: You are comfortable working at the intersection of velocity and discipline, understanding that in 2026, you cannot have one without the other.


Nice-to-Haves

  • Familiarity with load testing and performance testing tools
  • Exposure to compliance and security testing patterns (GDPR, data handling)
  • Additional languages beyond Python (TypeScript, JavaScript)
  • Background in localisation, language technology, or NLP-adjacent domains
  • Experience in smaller, fast-moving companies where you wear multiple hats



WHY THIS ROLE?

You won't be stuck in a repetitive manual testing loop. You’ll be building the AI-driven quality engine of a modern tech company. You’ll have a bird’s-eye view of the entire technical landscape, influencing the standards of every pod at Straker

If you’re the kind of person who sees AI as a tool to be wielded rather than a threat to be managed – this is the role for you!

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