Director of Quality Engineering

About the role

We are seeking a visionary engineering leader to shape and drive NiCE’s quality engineering discipline into the AI era. The Director will own automation infrastructure, performance engineering, and AI‑driven quality initiatives while building and mentoring high‑performing teams that set the standard for modern software validation at scale.

Key responsibilities

• Define and lead AI‑augmented quality strategy, including LLM‑powered test generation, triage, and root‑cause analysis.
• Own the end‑to‑end automation strategy across UI, API and integration layers; design scalable test frameworks and embed shift‑left testing in CI/CD pipelines (Jenkins, GitHub Actions).
• Establish coverage KPIs, flakiness SLAs and automation ROI metrics; drive adoption of self‑healing and AI‑assisted test maintenance.
• Lead performance and load testing at enterprise scale, define SLOs/SLAs, and collaborate with SRE on reliability thresholds.
• Build, grow and mentor teams of automation engineers, performance engineers and architects; set technical direction, OKRs and career ladders.
• Partner cross‑functionally with Product, DevOps and R&D leadership to embed quality into every stage of the software development lifecycle.

Required profile

• 12+ years of software engineering or QA experience, with at least 5 years in senior leadership (Director or senior staff) managing direct reports.
• Hands‑on expertise in designing and implementing test automation frameworks from the ground up.
• Proven track record delivering performance engineering for large‑scale, cloud‑native systems (10,000+ concurrent users).
• Experience shipping AI/ML‑related products and validating non‑deterministic model outputs.
• Strong ability to influence cross‑functional teams and champion responsible AI testing practices.

Required skills

• Test automation frameworks and tools (e.g., Selenium, Cypress, Playwright).
• CI/CD pipelines (Jenkins, GitHub Actions).
• LLM‑powered test generation and AI‑assisted testing tools (GitHub Copilot, Claude, custom agents).
• Performance and load testing tools (k6, JMeter, Gatling) and APM integrations.
• AI/ML model validation techniques and governance.
• Metrics definition (coverage KPIs, flakiness SLAs, ROI).