דרושים » אבטחת איכות QA » Quality Lead - AI-Native R&D

We are becoming an agentic ITSM leader - and we're rebuilding R&D to match. In our AI-native model, a managed, always-on "Machine" produces most of the code while small pods of engineers, PMs and designers direct, review, and govern it. In that world, quality isn't a phase - it's how the system is built.
We're hiring a Quality Lead to own that.
Why this role is different: you won't run a traditional QA team that tests features at the end. You'll own the quality gates inside the Machine and in production, author the monitoring skills our pods rely on, and hold independent authority to fail the Machine's output. Quality is our north star, and this role sets the bar.
THE MISSION: Make reliability, performance, and user experience a property of the system - not of individual heroics. Build and lead a Quality function (~9 people) that keeps an AI-native delivery org fast and trustworthy, and give the business confidence that what the Machine ships is safe to ship.
WHAT YOU'LL DO:
Own quality gates in the Machine - prose-driven tests (generated from requirements, not the code), adversarial / agent-checks-agent review, static analysis and code-quality remediation (e.g. SonarCloud), and CI gates that run before anything reaches a human.
Own quality in production - release verification, production testing, and ownership of change-fail and deployment-rework rates.
Author monitoring guidelines & reusable observability skills that delivery pods and the Machine consume - so monitoring is built in, not bolted on.
Own the evals that score the Machine's output for behavioral consistency and reliability - treating evaluation as a first-class engineering discipline.
Act as an independent governance voice - with the authority to block or fail output that doesn't meet the bar, partnering closely with Architecture.
Partner with the Core Platform team on the quality of customer-issue fixes and existing functionality.
Lead, coach and grow the team - quality/gate engineers, an agent-evaluation engineer, production-monitoring (SRE) and QA-infrastructure engineers.
Set the quality metrics and report them - DORA + deployment-rework rate, escaped-defect rate, review-queue depth, eval pass rates.
WHAT YOU'LL OWN (OUTCOMES)
Fewer regressions and less firefighting; faster resolution of customer issues.
Reliability, performance and UX that customers can count on.
A quality system trustworthy enough to let autonomous delivery scale safely.