QA Director

About the role

We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. The QA Director will own automation infrastructure, performance engineering, and AI‑driven quality initiatives, building and mentoring high‑performing teams.

Key responsibilities

• Define and lead 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 such as GitHub Copilot and Claude.
• Own the full automation strategy across UI, API, and integration layers.
• Architect scalable, maintainable test frameworks and drive shift‑left testing 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.
• 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.
• 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 R&D leadership.

Required profile

• 12+ years in software engineering or QA with 5+ years in engineering leadership at Director level.
• Deep hands‑on background in test automation architecture, having built frameworks from scratch.
• Proven track record leading performance engineering at scale (10,000+ concurrent users, cloud‑native environments).
• Experience shipping or operating AI/ML systems and understanding their unique quality challenges.
• Prior success managing multi‑team organizations (10–40+ total headcount).
• Enterprise software domain experience preferred (SaaS, CCaaS, fintech, or similar high‑uptime environments).
• Working knowledge of LLM capabilities, prompt engineering, RAG, and agentic workflows.
• Experience evaluating or integrating AI coding assistants (GitHub Copilot, Claude, etc.).
• Comfortable with statistical testing concepts such as model drift detection and data validation.
• 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).
• Exceptional communicator able to translate technical concepts into executive‑level strategy.
• Data‑driven decision maker who measures quality outcomes.
• Bias for hiring and developing senior talent and building lasting teams.

Required skills

• Python
• TypeScript
• Java
• Jenkins
• GitHub Actions
• LLM tools (GitHub Copilot, Claude)
• Prompt engineering, RAG, agentic workflows
• Statistical testing and model drift detection
• k6
• JMeter
• Gatling
• Datadog
• Grafana
• Dynatrace
• New Relic

What we offer

• Global, fast‑paced collaborative environment with endless internal career opportunities.
• Hybrid work model (NiCE‑FLEX): 2 days in office, 3 days remote each week.
• Equal opportunity employer committed to diversity and inclusion.