QA Director

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale.This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC - from the first commit to production monitoring.

You will be the organizational bridge between engineering velocity and product reliability.How will you make an impact? AI Quality StrategyDefine and lead all AI-augmented quality initiatives across the organizationDeploy LLM-powered test generation, triage, and root-cause analysis toolingBuild frameworks for validating AI/ML model outputs and non-deterministic behaviorsEvaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents)Champion responsible AI testing practices, coverage standards, and governance modelsAutomation EngineeringOwn the full automation strategy across UI, API, and integration layersArchitect scalable, maintainable test frameworks Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions)Establish coverage KPIs, flakiness SLAs, and automation ROI metricsLead adoption of self-healing and AI-assisted test maintenancePerformance EngineeringLead performance and load testing strategy at enterprise scaleDefine SLOs/SLAs and partner with SRE on reliability thresholdsDesign continuous performance validation integrated into delivery pipelinesDrive root-cause analysis for regressions, bottlenecks, and latency spikesOversee toolchain including k6, JMeter, Gatling, and APM integrationsPeople & Org LeadershipLead and grow teams of automation engineers, performance engineers, and architectsSet technical direction, OKRs, and career ladders for the quality engineering orgHire senior ICs and architect-level talent; build succession depthFoster a culture of ownership, engineering craft, and continuous learningPartner cross-functionally with Product, DevOps, and R&D leadership.דרישות: 12 years in software engineering or QA, with 5 years in engineering leadership at the Director level or senior Staff with direct reportsDeep hands-on background in test automation architecture - you've built frameworks from scratch, not just inherited themProven track record leading performance engineering at scale (10,000 concurrent users, distributed systems, cloud-native environments)Experience shipping or operating AI/ML systems and understanding the unique quality challenges they introducePrior success managing multi-team orgs with both IC engineers and architects (10-40 total headcount)Enterprise software domain experience strongly preferred (SaaS, CCaaS, fintech, or similar high-uptime/regulated environments)AI & Technical AcumenWorking knowledge of LLM capabilities and limitations relevant to software testing (prompt engineering, RAG, agentic workflows)Experience evaluating or integrating AI coding assistants (GitHub Copilot, Claude, Cursor, or equivalents) in engineering workflowsComfort with statistical testing concepts: model drift detection, data validation, behavioral testing for non-deterministic outputsProficient in at least one scripting/programming language (Python, TypeScript, Java) and modern CI/CD toolingFamiliarity with observability and APM tools (Datadog, Grafana, Dynatrace, New Relic)LeadershipExceptional communicator - able to translate deep technical concepts into executive-level strategy and roadmapsStrong organizational influencer who shapes culture and engineering standards beyond your direct orgData-driven decision maker: you measure quality outcomes, not just activityBias for hiring and developing senior המשרה מיועדת לנשים ולגברים כאחד.