Director Engineering - Automation, Performance and AI Quality (AI)

Location: Sandy, Utah, United States

Company

hirify.global develops AI, cloud, and digital software used by more than 25,000 global businesses for customer experience, financial crime prevention, and public safety; the company has more than 8,500 employees across 30+ countries.

What you will do

• Define and lead AI-augmented quality initiatives, including LLM-powered test generation, triage, root-cause analysis, and responsible AI testing governance.
• Own automation strategy across UI, API, and integration layers; architect scalable test frameworks and embed shift-left testing into Jenkins and GitHub Actions CI/CD pipelines.
• Lead enterprise-scale performance and load testing, define SLOs and SLAs with SRE, and integrate continuous performance validation into delivery pipelines.
• Drive root-cause analysis for regressions, bottlenecks, latency spikes, and non-deterministic AI/ML behavior using performance, observability, and APM tooling.
• Lead and grow teams of automation engineers, performance engineers, and architects; set technical direction, OKRs, career ladders, and succession depth.
• Partner with Product, DevOps, and R&D leadership to connect engineering velocity with product reliability.

Requirements

• 12+ years of experience in software engineering or QA, including 5+ years in engineering leadership at Director level or senior Staff+ level with direct reports.
• Deep hands-on experience building test automation frameworks from scratch and leading automation architecture.
• Proven experience leading performance engineering at scale, including 10,000+ concurrent users, distributed systems, and cloud-native environments.
• Experience shipping or operating AI/ML systems and understanding their quality challenges.
• Experience managing multi-team organizations of 10–40+ IC engineers and architects.
• Working knowledge of LLM capabilities and limitations for software testing, including prompt engineering, RAG, and agentic workflows.
• Experience evaluating or integrating AI coding assistants such as GitHub Copilot, Claude, Cursor, or equivalents.
• Knowledge of statistical testing concepts, model drift detection, data validation, and behavioral testing for non-deterministic outputs.
• Proficiency in at least one of Python, TypeScript, or Java, plus modern CI/CD tooling; familiarity with Datadog, Grafana, Dynatrace, or New Relic.
• Exceptional communication, executive-level technical strategy skills, organizational influence, data-driven decision-making, and the ability to operate in ambiguity.

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• Enterprise software domain experience, particularly SaaS, CCaaS, fintech, or other high-uptime or regulated environments.

Culture & Benefits

• Culture focused on ownership, engineering craft, continuous learning, and high quality standards.
• Opportunity to modernize legacy testing paradigms and introduce agentic test generation, self-healing testing, and AI-assisted maintenance.
• Equal opportunity employment across protected characteristics.