Director of Engineering, Automation, Performance & AI Quality

About the role

We are seeking a visionary engineering leader to define and drive AI‑augmented quality engineering across the organization. The role owns automation infrastructure, performance engineering, and AI‑driven quality initiatives, building high‑performing teams that set the standard for modern software validation at scale.

Key responsibilities

• Define and lead AI‑augmented quality strategy, deploying LLM‑powered test generation, triage and root‑cause analysis tools.
• Own the end‑to‑end automation strategy for UI, API and integration testing, architecting scalable test frameworks and embedding shift‑left testing in CI/CD pipelines.
• Lead performance and load testing at enterprise scale, set SLOs/SLAs, and collaborate with SRE on reliability thresholds.
• Build and mentor teams of automation engineers, performance engineers and architects, establishing technical direction, OKRs and career ladders.
• Evaluate and integrate emerging AI quality toolchains such as GitHub Copilot, Claude and other agents, championing responsible AI testing practices.

Required profile

• 12+ years of software engineering or QA experience with at least 5 years in senior engineering leadership.
• Deep hands‑on experience building test automation frameworks from scratch and leading performance engineering for large‑scale, cloud‑native systems.
• Proven track record delivering AI/ML systems and addressing their unique quality challenges.
• Experience managing multi‑team organizations of 10–40+ engineers and architects.
• Strong communication skills and ability to influence cross‑functional stakeholders.

Required skills

• Python, TypeScript, Java
• CI/CD tools: Jenkins, GitHub Actions
• Performance testing tools: k6, JMeter, Gatling
• Observability and APM platforms: Datadog, Grafana, Dynatrace, New Relic
• LLM technologies and AI coding assistants (GitHub Copilot, Claude)
• Statistical testing concepts, model drift detection, data validation

What we offer

• Hybrid work model (2 days onsite, 3 days remote) for maximum flexibility.
• Opportunities to grow within a global market‑leading company with internal career paths across many domains.
• Access to cutting‑edge AI, cloud and digital technologies.