Director of Quality Engineering

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. So, what’s the role all about? 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 Strategy Define and lead all AI-augmented quality initiatives across the organization Deploy LLM-powered test generation, triage, and root-cause analysis tooling Build frameworks for validating AI/ML model outputs and non-deterministic behaviors Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents) Champion responsible AI testing practices, coverage standards, and governance models Automation Engineering Own the full automation strategy across UI, API, and integration layers Architect scalable, maintainable test frameworks Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions) Establish coverage KPIs, flakiness SLAs, and automation ROI metrics Lead adoption of self-healing and AI-assisted test maintenance Performance Engineering Lead performance and load testing strategy at enterprise scale Define SLOs/SLAs and partner with SRE on reliability thresholds Design continuous performance validation integrated into delivery pipelines Drive root-cause analysis for regressions, bottlenecks, and latency spikes Oversee toolchain including k6, JMeter, Gatling, and APM integrations People Org Leadership Lead and grow teams of automation engineers, performance engineers, and architects Set technical direction, OKRs, and career ladders for the quality engineering org Hire senior ICs and architect-level talent; build succession depth Foster a culture of ownership, engineering craft, and continuous learning Partner cross-functionally with Product, DevOps, and RD leadership Have you got what it takes? 12+ years in software engineering or QA, with 5+ years in engineering leadership at the Director level or senior Staff+ with direct reports Deep hands-on background in test automation architecture — you've built frameworks from scratch, not just inherited them Proven 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 introduce Prior 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 Acumen Working 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 workflows Comfort with statistical testing concepts: model drift detection, data validation, behavioral testing for non-deterministic outputs Proficient in at least one scripting/programming language (Python, TypeScript, Java) and modern CI/CD tooling Familiarity with observability and APM tools (Datadog, Grafana, Dynatrace, New Relic) Leade ... (truncated, view full listing at source)