Overview
Lead enterprise Incident and Problem Management with a focus on architecting and operationalizing Agentic AI solutions within the ITSM ecosystem. The role aims to design and deploy autonomous AI agents for incident management and drive continuous improvement through analytics and AI-generated insights.
Key Responsibilities
- Lead the design and implementation of Agentic AI operating models for autonomous service management workflows.
- Serve as a trusted advisor on service stability, agentic automation strategy, and systemic risk.
- Drive continuous improvement using analytics, AI-generated insights, and agent feedback loops.
- Establish and oversee metrics, KPIs, and KRIs for operational resilience and AI risk management.
- Architect and deploy Agentic AI systems for autonomous incident classification, routing, investigation, and resolution.
- Design agent orchestration frameworks for coordinated AI agent tasks.
- Oversee real-time monitoring and dashboards using AIOps platforms and ServiceNow.
- Establish governance and traceability standards for agentic decision-making.
- Oversee incidents involving AI-enabled and agent-driven services.
- Maintain and evolve incident runbooks and playbooks.
- Monitor SLA/SLO attainment and AI risk indicators.
- Deploy Agentic AI for autonomous root cause analysis, pattern recognition, and proactive remediation.
- Establish and monitor KRIs for problem management.
- Lead problem review forums.
- Oversee investigations of AI-enabled services.
- Establish a tiered reporting framework enhanced with AI-driven insights.
- Design, define, and standardize AI-enabled KPIs and KRI models.
- Leverage advanced analytics and agentic AI to identify emerging service risks and predict service degradation.
- Govern the use of AI-generated insights and automated reporting.
Required Experience
- Master’s degree with 5 years of experience or bachelor’s degree with 7 years of relevant experience in computer science, IT, engineering, or a related field.
- Hands-on experience designing, deploying, and governing Agentic AI systems, including multi-agent orchestration frameworks, autonomous workflow design, and agent lifecycle management.
- Deep expertise in AIOps platforms, observability tooling, and AI-driven automation for incident and problem management.
- Experience managing incidents across AI-enabled services and autonomous agent pipelines, including failure mode analysis and agent oversight.
- Familiarity with AI agent frameworks such as LangGraph, AutoGen, CrewAI, or equivalent enterprise orchestration tools.
- Experience governing Incident and Problem Management in Azure DevOps (ADO), DevOps, and product-centric environments.
- Deep understanding of ITIL® 4 in Agile and SAFe environments.
- Familiarity with ITIL® 4 Incident and Problem Management practices.
- Experience managing incidents and problems across AI-enabled service frameworks, including AI platforms, automated workflows, data pipelines, and autonomous operations.
Qualifications
- Master’s degree or bachelor’s degree in computer science, IT, engineering, or a related field.
- Any recognized certification in AI engineering, agentic systems, or intelligent automation.
- Microsoft Azure AI Engineer Associate.
- Google or Coursera Agentic AI practitioner certificates (e.g., LangGraph, AutoGen).
- AI Governance, Responsible AI.
