Manager-Digital Experience & Insights Lead

NCRi Solutions is looking for a Manager-Digital Experience & Insights Lead for one of the biggest Conglomerate clients based in UAE to improving the performance, reliability, and user experience of digital platforms through application-level insights, AI/ML-driven analytics, and quality engineering innovations. This role operates within the digital product and engineering space, delivering actionable insights and intelligent automation directly tied to the development, testing, and performance of web and mobile applications.

Key Responsibilities:

• Background in driving DevOps, CI/CD maturity, and observability adoption across development and testing functions
• Strong in AI/ML for applications, particularly in QA automation, performance optimization, and AIOps.
• Hands-on experience with Python, SQL, TensorFlow/PyTorch, REST APIs, and app telemetry tools.
• Expertise in QA frameworks (e.g., Selenium, TestNG, Appium), test orchestration (e.g., Xray, Zephyr), and CI/CD platforms.
• Familiarity with application observability and APM tools (e.g., Datadog, Dynatrace, Prometheus, Splunk).
• Deep architectural understanding of microservices, mobile apps, and frontend/backend integrations.
• Ability to derive product insights from session analytics, log aggregation, heatmaps, and tracing tools.
• Strong problem-solving and communication skills to translate application performance data into engineering and business impact.

Core Competencies:

• 8+ years of experience in digital experience, QA engineering, application performance, or platform monitoring roles.
• Demonstrated success in applying ML to solve QA, testing, or application telemetry challenges.
• Hands-on experience managing high-performance teams across QA, test automation, observability, and application analytics.
• Proven track record in shortening release cycles, reducing defect rates, and improving app stability.
• Experience integrating ML models into engineering workflows (e.g., predictive testing, auto healing, anomaly detection)

Education & Certification:

• Master’s degree in Computer Science, Software Engineering, or a related discipline (preferred)
• Certifications in AI / ML related (preferred)
• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related field (or equivalent academic background)

Job Type: Full-time

Work Location: In person