Head of AI-OPS & Automation

Job description

About the role Our Mission: We run 24/7 global tech supporting life-critical medical and security services worldwide. Our Shift: We are moving from manual, reactive support to smart, AI-driven operations. Our Culture: We value purpose, ownership, and real-world impact over hierarchy in a fast-evolving global team. The Mission: A senior, hands-on IT Shared Services leader to build and scale modern automation and AIOps tools. The Focus: Stop maintaining old systems—build what is next, use AI to simplify operations, and stop issues before they happen. Job Responsibilities Strategy & AI Set Roadmap: Own AIOps and automation strategy. Target Impact: Prioritize high-value, practical AI use cases. Prove Value: Balance quick wins with scalable solutions. Smart Operations Build Observability: Design cloud and infrastructure monitoring. Detect Early: Use AI to spot data patterns and risk signals. Reduce Noise: Turn high alert volumes into actionable insights. Scaled Automation Cut Manual Tasks: Replace repetitive work with orchestration. Auto-Remediate: Drive self-healing systems and self-service. Embed Workflows: Integrate automation into daily operations. Leadership Lead Engineers: Manage the automation and AIOps engineering team. Foster Culture: Drive continuous learning and ownership. Partner Globally: Align with cloud, security, and vendors. Job Requirements Required Work Experience Experience in IT operations, automation, platform, or AIOps‑related roles. Experience delivering automation or data‑driven improvements in production environments. Experience working with regional or global systems is a plus. We do not require a specific number of years. We care about what you’ve built, improved, and learned. Required Qualifications Degree or equivalent experience in Computer Science, Engineering, IT, Data, or related fields. Cloud, automation, or AI‑related certifications are welcome but not mandatory. Continuous learning is strongly valued. Skills Required Technical Skills Solid understanding of modern IT environments (cloud, hybrid, SaaS). Practical experience with automation, orchestration, or platform integration. Working knowledge of AIOps concepts, observability, telemetry, and analytics. Comfortable working with data (logs, metrics, events) at scale. AI & Innovation Mindset Hands‑on exposure to AI, machine learning, or advanced analytics in real systems. Interest in using AI to solve operational problems — not just building models. Curious, experimental, and willing to test new ideas. Ways of Working Comfortable taking ownership and making decisions. Able to work in fast‑moving, evolving environments. Strong communication skills — simple, clear, and practical.