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., ServiceNow).
• Embed AI-driven insights into Major Incident Management processes.
General functional responsibilities:

• 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.
Core competencies required:

• Technical Leadership
• Deep expertise in observability frameworks (metrics, logs, traces, events, topology).
• Strong knowledge of OpenTelemetry 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.