AI Ops Technical Leader
Tasks
- Apply MLOps model monitoring and drift detection
- Automate L1 triage and predict major incidents
- Build predictive alerting
- Collaborate with operations support and DS and AI teams on solution delivery
- Conduct architecture reviews proof of concept and vendor evaluation
- Create ticket clustering and auto triage
- Deliver knowledge mining and intelligent runbooks
- Design AI enabled features for ServiceNow and ITSM platforms
- Develop change risk scoring
- Develop real time incident enrichment
- Ensure reliability low latency auditability explainability and zero downtime deployments
- Generate post mortems and improve shift handovers
- Identify and prioritize AI use cases to reduce MTTR and MTTD
- Implement automated rollback performance checks and cost optimization
- Implement automated root cause analysis
- Integrate AIOps tools with ITSM monitoring and ticketing systems
- Lead AIOps platform architecture and continuous improvement
- Lead data and AI initiatives for operations support
- Lead squad mentoring technical coaching and code reviews
- Serve as AI technical authority for operations support transformation
Perks/Benefits
- N/A
Skills/Tech-stack
Anomaly Detection | Apache Airflow | Apache Kafka | Apache Spark | Automated Actions | Azure | Azure Data | Azure Data Factory | BigPanda | Data Factory | Databricks | Datadog | Drift Detection | Dynatrace | ELK Stack | Event Correlation | GenAI | Grafana | ITIL | ITSM | Jira Service | Jira Service Management | LLM | Language Models | Large Language Models | MLOps | Model Monitoring | Moogsoft | Observability | Predictive Analytics | Prometheus | PyTorch | Python | Service Management | ServiceNow | Splunk | TensorFlow
Education
N/A
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