Job Summary: We are looking for a skilled ServiceNow ITOM Developer with 36 years of experience to join our IT operations team. The ideal candidate will have hands-on expertise in implementing and supporting ITOM modules like Discovery, Service Mapping, Event Management, and CMDB integrations within the ServiceNow platform. Key Responsibilities: Develop, configure, and maintain ITOM modules in ServiceNow, especially: Discovery Service Mapping Event Management CMDB integration and health Integrate with various infrastructure and monitoring tools (e.g., SolarWinds, Nagios, SCOM, etc.) Collaborate with platform architects, ITSM/CMDB teams to ensure data accuracy and compliance Customize patterns and probes for accurate infrastructure discovery Create and manage MID Server configurations and troubleshooting Support ongoing enhancement and optimization of ITOM processes and dashboards Maintain proper documentation and follow ITIL practices Required Skills: 3 to 6 years of hands-on experience in ServiceNow ITOM Strong experience in ServiceNow Discovery , CMDB , and Service Mapping Knowledge of Event Management and integration with monitoring tools Familiarity with MID Server installation and troubleshooting Good understanding of network topologies, cloud infrastructure (AWS, Azure), and on-prem environments Proficiency in JavaScript , Glide API , and REST/SOAP Integrations Experience with CMDB data models and CI class structures Preferred Qualifications: ServiceNow Certified Implementation Specialist – ITOM Experience with Agile/Scrum methodology Basic scripting and automation experience (PowerShell, Python, etc.) Exposure to other ServiceNow modules (e.g., ITSM, SecOps) is a plus

Build automated ML pipelines for training, validation, deployment, and monitoring using Vertex AI Pipelines, Kubeflow, or TFX Leverage Vertex AI Workbench, Training, and Experiments for reproducible, collaborative model development Deploy, manage, and monitor models using Vertex AI Model Registry, Model Monitoring, and Prediction Endpoints Collaborate with Data Scientists to productionize notebooks and prototypes into scalable ML services Monitor model performance, detect data/model drift, and ensure data quality using Vertex AI Monitoring Containerize and orchestrate ML workloads using Docker and Kubernetes (GKE) Build and maintain robust CI/CD pipelines using Cloud Build, Jenkins, or Bitbucket Pipelines Ensure strong version control, security, and compliance across the ML lifecycle Maintain comprehensive documentation, templates, and artifacts to enable reproducibility, governance, and fast onboarding