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As Chief Agentic Quality Architect, you will orchestrate the transition from traditional scripted testing to an AI-augmented quality ecosystem. Your primary goal is to leverage agentic AI tools to generate, execute, and maintain high-fidelity test suites that keep pace with a development environment where AI agents are writing a significant portion of the production code.
WHAT YOU'LL DO
- Take ownership of a new product or suite of products as a hands-on quality leader. Conduct a comprehensive audit of the existing test estate across all layers — unit, integration, API, UI, sanity, and regression — evaluating depth, coverage, and reliability of each suite.
- Evaluate the current QA tooling, frameworks, and automation maturity against company quality benchmarks and coverage expectations. Identify systemic gaps, test debt, and high-risk areas with no automated coverage.
- Produce a Current State & Gap Coverage Report that maps existing tooling, highlights missing coverage domains, and recommends the adoption tooling needed to close the gaps — the baseline for every roadmap that follows.
- Define missing test cases and user journeys. Prioritise end-to-end automation across critical business flows using agentic automation patterns, with a deliberate emphasis on left-heavy coverage — maximising unit and integration depth first, and extending rightward through black-box UI and regression testing.
- Architect and own the phased quality engineering roadmap, structured as three delivery horizons:
- Two-Week Plan: Complete the current-state assessment; identify the highest-risk coverage gaps; stand up quick-win automation on the most critical user journeys; evaluate and select the tooling to be adopted.
- One-Month Plan: Core regression coverage established across primary domains; CI/CD quality gates operational and integrated into the development pipeline; agentic test generation producing its first validated suites.
- Three-Month Plan: End-to-end agentic automation live and self-maintaining; company benchmark coverage achieved; AI guardrails enforced across all automated agent output; quality metrics visible to engineering leadership.
- Prompt-Based Engineering: Utilise AI agents to automatically transform business requirements and manual test cases into executable Playwright or Cypress scripts.
- Synthetic Test Creation: Implement tools that autonomously generate test data and edge-case scenarios that human testers might overlook.
- Autonomous Maintenance: Deploy self-healing automation frameworks that use AI to detect UI changes and update test selectors without human intervention.
- Agent Regression Strategy: Design and own a comprehensive regression suite specifically tuned to catch the non-deterministic “hallucinations” or logic errors common in AI-generated code.
- Behavioral Locking: Implement characterisation testing patterns to “lock in” the expected behaviour of legacy systems during AI-assisted refactoring.
- Autonomous Output Validation: Define quality gates to validate the outputs of autonomous agents, ensuring they meet functional, security, and performance boundaries.
WHAT WE'RE LOOKING FOR
- Automation Frameworks: Expert-level proficiency in Playwright, Cypress, or Selenium.
- AI Tooling: Hands-on experience using LLMs (Claude, GPT-4, etc.) and agentic frameworks to generate code or automate workflows.
- CI/CD Mastery: Deep understanding of integrating quality gates into AWS-based pipelines or similar environments.
- Architectural Mindset: Ability to design "Behavioral Snapshots" to safeguard critical business logic during rapid transformations.
- 10+ years in QA automation engineering, SDET, or test architecture roles
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