Director, AI Quality & Automation Engineering

NICE; Utah; Vor Ort; USD 180.000 - 280.000; Vollzeit

Zusammenfassung

NiCE is seeking a visionary Director of Engineering to architect and lead the automation, performance, and AI quality disciplines. You will own automation infrastructure, drive AI-driven quality initiatives, and build high-performing teams that set the standard for validation at scale.

You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking across the SDLC—from commit to production monitoring.

Qualifikationen

• 12+ years in software engineering or QA, with leadership experience
• Hands-on background in test automation architecture
• Proven track record leading performance engineering at scale
• Experience shipping or operating AI/ML systems and understanding quality challenges

Aufgaben

• Define and lead AI quality strategy across the organization
• Deploy LLM-powered test generation, triage, and root-cause tooling
• Build frameworks for validating AI/ML model outputs and non-deterministic behaviours
• Evaluate and integrate AI quality tools and governance models
• Own the full automation strategy across UI, API, and integration layers
• Architect scalable, maintainable test frameworks and CI/CD integration
• Define SLOs/SLAs and partner with SRE on reliability thresholds
• Drive performance testing strategy at enterprise scale
• Lead and grow teams of automation and performance engineers

Kenntnisse

Test automation architecture

Performance engineering

AI quality strategy

Leadership

Cross-functional collaboration

CI/CD tooling

Tools

Datadog

Grafana

Dynatrace

New Relic

GitHub Copilot

Jobbeschreibung

NiCE is seeking a visionary Director of Engineering to architect and lead the automation, performance, and AI quality disciplines. You will own automation infrastructure, drive AI-driven quality initiatives, and build high-performing teams that set the standard for validation at scale.

You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking across the SDLC—from commit to production monitoring.