Director of Engineering (AI Quality)

TL;DR

Director of Engineering (AI Quality): Architect and lead quality engineering discipline into the AI era, owning automation infrastructure, performance engineering, and all AI-driven quality initiatives with an accent on agentic test generation and embedding AI-quality thinking into SDLC. Focus on disrupting legacy testing paradigms, building scalable frameworks, and validating AI/ML model outputs.

Location: Hybrid in Raanana, Israel (2 days office, 3 days remote)

Company

Market-leading NASDAQ-listed software company providing AI-powered solutions for customer experiences, financial crime prevention, and public safety, serving 25,000+ global businesses with 8,500 employees across 30+ countries.

What you will do

• Define and lead AI-augmented quality initiatives, deploying LLM-powered test generation, triage, and root-cause analysis tooling
• Own full automation strategy across UI, API, and integration layers, architecting scalable test frameworks and shift-left testing in CI/CD
• Lead performance and load testing at enterprise scale, defining SLOs/SLAs and continuous validation in pipelines
• Build and mentor high-performing teams of automation, performance engineers, and architects; set technical direction and OKRs
• Partner cross-functionally with Product, DevOps, and R&D leadership to bridge engineering velocity and product reliability

Requirements

• 12+ years in software engineering or QA, 5+ years in engineering leadership at Director level or senior Staff+ with direct reports
• Deep hands-on experience building test automation frameworks from scratch
• Proven track record leading performance engineering at scale (10,000+ concurrent users, distributed/cloud-native systems)
• Experience with AI/ML systems and their quality challenges; working knowledge of LLMs, prompt engineering, RAG, agentic workflows
• Managing multi-team orgs (10–40+ headcount); enterprise software domain (SaaS, CCaaS, fintech) preferred
• Proficient in Python/TypeScript/Java, CI/CD tooling, observability/APM (Datadog, Grafana)

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• Experience evaluating/integrating AI coding assistants (GitHub Copilot, Claude)
• Statistical testing for non-deterministic outputs, model drift detection

Culture & Benefits

• hirify.global-FLEX hybrid model: 2 office days for collaboration, 3 remote days weekly
• Fast-paced, collaborative environment with top talent and endless internal career opportunities
• Focus on innovation, continuous learning, and raising the bar in AI, cloud, and digital domains
• Equal opportunity employer committed to diversity and inclusion