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Quality Engineering Director
ГибридПолная занятостьQA & Test AutomationEnterprise SoftwareCustomer Experience SoftwarePublic Safety Technology
Lead the quality engineering discipline for a global enterprise software organization. Own AI-driven quality strategy, automation infrastructure, performance engineering, and the growth of teams spanning automation, performance, and architecture. This hybrid role is based in Israel, with two office-
Обязанности
- Define and lead AI-augmented quality initiatives across the organization
- Deploy LLM-powered test generation, triage, and root-cause analysis tools
- Create approaches for validating AI/ML outputs and non-deterministic behavior
- Evaluate and integrate emerging AI quality toolchains
- Set responsible AI testing practices, coverage standards, and governance models
- Own automation strategy across UI, API, and integration layers
- Architect scalable test frameworks and embed shift-left testing in CI/CD pipelines
- Establish coverage KPIs, flakiness service levels, and automation ROI metrics
- Lead enterprise-scale performance and load testing
- Define reliability thresholds and partner with SRE on SLOs and SLAs
- Integrate continuous performance validation into delivery pipelines
- Analyze regressions, bottlenecks, and latency spikes
- Set technical direction, objectives, and career frameworks for the quality engineering organization
- Hire and develop senior individual contributors, architects, and engineering managers
- Build succession depth and foster a culture of ownership, engineering quality, and continuous learning
- Partner with Product, DevOps, and R&D leadership
Требования
- 12+ years of software engineering or quality assurance experience
- 5+ years of engineering leadership at Director level or senior Staff level with direct reports
- Hands-on experience designing test automation architectures and building frameworks from the ground up
- Track record leading performance engineering at enterprise scale, including distributed systems and cloud-native environments
- Experience shipping or operating AI/ML systems and addressing their quality challenges
- Experience managing multi-team organizations of engineers and architects, typically totaling 10–40+ people
- Working knowledge of LLM capabilities and limitations, prompt engineering, retrieval-augmented generation, and agentic workflows
- Knowledge of model drift detection, data validation, statistical testing, and behavioral testing for non-deterministic outputs
- Proficiency in Python, TypeScript, or Java and modern CI/CD tooling
- Executive-level communication, organizational influence, and data-driven decision-making
Будет плюсом
- Enterprise software experience, particularly SaaS, contact-center software, financial technology, or other high-availability or regulated environments
- Experience evaluating AI coding assistants such as GitHub Copilot, Claude, or Cursor
- Knowledge of observability and application-performance tools such as Datadog, Grafana, Dynatrace, or New Relic
Условия и преимущества
- Hybrid work model with two office days and three remote days per week
- Collaborative, global environment with learning and internal career opportunities
- Equal opportunity employment