Principal Lead, Observability & AI Ops

Role specific responsibilities

• Define and implement the enterprise observability blueprint
• Define SLI/SLO frameworks in collaboration with engineering teams
• AIOps Enablement
• Implement AI-driven event correlation and incident prioritisation
• Lead reduction of P1/P2 incidents through improved detection and prevention
• Design real-time operational dashboards for executive reporting
• Ensure seamless integration with ITSM platforms (e.g., Service Now)
• Embed AI-driven insights into Major Incident Management processes

• Lead and develop a high-performing Observability & AIOps team
• Manage budgets, vendor contracts, and technology roadmaps
• Collaborate with Enterprise Architecture, Cloud, Security, and Application Engineering functions
• Ensure alignment with ITIL, SRE, and enterprise governance frameworks
• Report on operational health metrics to senior leadership and risk committees
• Champion a culture of automation, reliability engineering, and data‑driven operations
• Support audit, regulatory, and resilience testing requirements

• Technical Leadership
• Deep expertise in observability frameworks, metrics, logs, traces, events, topology
• Strong knowledge of Open Telemetry standards and distributed tracing models
• Experience with enterprise monitoring stacks (e.g., Splunk)
• Practical implementation of AIOps platforms, AI & Data Analytics
• Event correlation, anomaly detection, noise reduction, and root cause analytics
• Familiarity with machine learning models in operations
• Data engineering fundamentals for telemetry pipelines
• Experience building automation workflows using orchestration tools and scripting
• Governance & Architecture tool rationalisation and vendor management experience