AIOps Support Engineer

·      Monitor and respond to production incidents, alerts, and service disruptions.

·      Investigate issues, perform impact assessment, and identify root causes.

·      Create, update, and track incidents through ServiceNow until closure.

·      Coordinate with Product Teams, vendors, Site IT teams, and stakeholders to resolve issues.

·      Escalate incidents according to the support model and escalation matrix.

·      Maintain operational documentation, troubleshooting guides, and knowledge articles.

·      Provide incident status updates and support root cause analysis (RCA) and continuous improvement activities.

·      Monitor application, infrastructure, API, and service health.

·      Respond to alerts and investigate abnormal system behavior or potential service issues.

·      Perform proactive monitoring and health checks to help prevent business impact.

·      Maintain monitoring tools, dashboards, and related documentation.

·      Continuously improve monitoring effectiveness and alert quality.

·      Perform AI Factory deployments to the Amazon Web Services (AWS) cloud in Staging (STG) and Production (PRD) environments.

·      Monitor deployment pipeline execution and resolve pipeline-related failures.

·      Develop and maintain the Continuous Integration and Continuous Deployment (CI/CD) pipeline in Microsoft Azure.

·      Maintain deployment procedures and pipeline documentation.

Coordinate deployment schedules, approvals, validation, and rollback activities with the relevant teams

·      Understanding of application monitoring, alerting, incident management, and support workflows.

·      Troubleshooting skills for web applications, APIs, and cloud-hosted services.

·      Familiarity with Structured Query Language (SQL), databases, Linux, and Microsoft Windows.

·      Knowledge of Representational State Transfer (REST) APIs and web services.

·      Exposure to AI Agents, Generative Artificial Intelligence (Generative AI), Python, Vue.js, AWS, Docker, and containerized applications.

·      Familiarity with monitoring and observability tools such as Grafana, AWS CloudWatch, Power BI, Splunk, or similar platforms.

·      Understanding of Machine Learning Operations (MLOps), Information Technology Infrastructure Library (ITIL), Site Reliability Engineering (SRE), or Development Operations (DevOps) is an advantage.