AIOps Engineer - SysTechuss

Job highlights

• The candidate should be able to design and deploy automation pipelines that enhance observability,predictive incident management,and self-healing systems.
• Preferred Technical Add-ons
• Strong coding experience in Python for automation scripts,data processing,and integration
• Experience with machine learning frameworks (PyTorch,TensorFlow,Scikit-learn)

with hands-on expertise in programming, workflow automation, and integration of AI-driven insights into IT operations. The candidate should be able to design and deploy automation pipelines that enhance observability, predictive incident management, and self-healing systems.

Core Technical Capabilities

• Strong coding experience in Python for automation scripts, data processing, and integration.
• Hands-on in Java (Spring/Maven) for enterprise-grade backend automation solutions.
• Solid JavaScript/TypeScript development with frameworks such as Node.js, Angular for building dashboards, portals, or automation UIs.
• Expertise in GitHub Workflows/Copilot for automated pipeline creation and code generation.
• Exposure to Azure AI Studio for integrating AI/ML models into operational workflows.
• Familiarity with AIOps concepts: anomaly detection, root cause analysis, log/event correlation.
• Understanding of observability pipelines (metrics, logs, traces).

Preferred Technical Add-ons

• Experience with machine learning frameworks (PyTorch, TensorFlow, Scikit-learn).
• Hands-on with monitoring and observability tools (Splunk, Dynatrace, Datadog, New Relic).
• Knowledge of cloud-native platforms (Azure, AWS, GCP) and microservices deployments.