Role & responsibilities

Key Responsibilities

- Customer Discovery, Adoption & Operationalization: Lead discovery and onboarding workshops; assess infrastructure, applications, cloud, observability, ITSM, incident, problem, change, and support processes; define maturity baseline, target operating model, use cases, rollout roadmap, adoption plan, service ownership, support boundaries, escalation paths, runbooks, production-readiness criteria, and transition-to-run controls.
- Observability & Operational Intelligence: Enable end-to-end operational visibility by integrating metrics, logs, traces, events, alerts, topology, service health, and operational context; operationalize event intelligence, alert prioritization, incident prediction, AI-assisted triage, RCA, remediation recommendations, operational copilots, and agent-assisted decision-making.
- Workflow Automation & Self-Healing: Design and implement intelligent routing, ticket enrichment, notifications, approvals, escalations, handoffs, closures, runbook automation, and self-healing workflows; define guardrails, approval mechanisms, risk tiers, rollback controls,



and effectiveness measures for automated remediation.
- Operational Knowledge & AI Enablement: Curate and govern runbooks, SOPs, knowledge articles, CMDB data, service maps, architecture documentation, incident history, known-error records, and resolution evidence to power agents, workflows, and AI-driven operations.
- Governance & Value Realization: Establish access controls, human-in-the-loop checkpoints, auditability, traceability, data-handling policies, and governance for AI recommendations and actions; track adoption, automation coverage, ticket deflection, alert-noise reduction, self-healing success, MTTA, MTTR, incident recurrence, service availability, operational efficiency, and cost outcomes.
- Stakeholder Management & BAU Transition: Serve as the primary interface between customer operations teams and AI Platforms, engineering, and delivery teams; lead adoption reviews, remove onboarding barriers, enable self-service, transfer knowledge, and transition governed BAU ownership to customer teams.

📌 AI Platform Adoption Engineer - Run (Kolkata)
🏢 Cognizant
📍 Kolkata