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Cynet Systems
AI-Ops EngineerCynet Systems • Fremont, CA
AI-Ops Engineer

AI-Ops Engineer

Cynet Systems • Fremont, CA
30+ days ago
Job type
  • Full-time
Job description

Job Description:

Pay Range: $55hr - $60hr

Experience Requirements:
  • 5+ years in IT Operations, Data Engineering, or related fields.
  • Experience in Azure Data Services, ETL/ELT processes, and ITIL-based operations.
  • 2+ years in AIOps implementation, monitoring, and automation.
Qualifications:
  • Bachelor’s or master’s degree in computer science, Engineering, or a related field.
Key Skills:
  • Client, PowerShell, or Python, Alerts & Logs Monitoring, Confluence and SharePoint
Skill Requirements:
  • Basic Understanding of Azure Data Services (ADF, Synapse, Databricks).
  • Experience in monitoring alerts from data pipelines (Azure Data Factory, Synapse, ADLS, MS Fabric etc.)
  • Familiarity with ETL/ELT concepts, data validation, and pipeline orchestration.
  • Experience in identifying failures in ETL jobs, scheduled loads, and streaming data services.
  • Hands-on experience with IT monitoring tools (e.g. Client, Azure Monitor, Dynatrace, or similar tools).
  • Skilled in creating and updating runbooks and SOPs.
  • Familiarity with data refresh cycles, batch vs. streaming differences.
  • Familiarity with ITIL processes for incident, problem, and change management.
  • Strong attention to detail, ability to follow SOPs, and effective communication for incident updates.
  • Solid understanding of containerized services (Docker/Kubernetes) and DevOps pipelines (Azure DevOps, GitHub Actions), always with an eye on data layer integration.
  • Proficiency in Jira, Confluence and SharePoint for status updates and documentation.
  • Understanding of scripting (PowerShell, Python, or Shell) for basic automation tasks.
  • Ability to interpret logs and detect anomalies proactively.
  • Analytical thinking for quick problem identification and escalation.
Preferred:
  • Exposure to CI/CD for data workflows, real-time streaming (Event Hub, Kafka).
  • Understanding of Data governance and compliance basics.
  • Experience with anomaly detection, time-series forecasting, and log analysis.
Key Responsibilities:
  • Monitor and support data pipelines on Azure Data Factory, Databricks, and Synapse.
  • Perform incident management, root-cause analysis for L1 issues, and escalate as needed.
  • Surface issues clearly & escalate to appropriate SME teams so they can be fixed at the root — avoid repetitive short fixes.
  • Identify whether issues are at pipeline level, data source level, or infrastructure level and route accordingly.
  • Document incident resolution patterns for reuse.
  • Acknowledge incidents promptly and route them to the correct team.
  • Execute daily health checks, maintain logs, and update system status in collaboration tools.
  • Work strictly as per SOPs documented by the team.
  • Maintain and update SOPs, runbooks, and compliance documentation.
  • Update system health status every 2 hours during the shift in Confluence or SharePoint.
  • Update incident status every 4 hours for P1/P2 tickets.
  • Complete service tasks on time as per SLA to release queues quickly.
  • Ensure compliance with enterprise data security, governance, and regulatory requirements.
  • Collaborate with data engineers, analysts, DevOps/SRE teams and business teams to ensure reliability and security.
  • Implement best practices in ML operations and productionization.

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AI-Ops Engineer • Fremont, CA

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