Posted:1 day ago|
Platform:
Work from Office
Full Time
Key Responsibilities:
Deliver engaging and interactive training sessions (24 hours total) based on structured modules.Teach integration of monitoring, logging, and observability tools with machine learning.Guide learners in real-time anomaly detection, incident management, root cause analysis, and predictive scaling.Support learners in deploying tools like Prometheus, Grafana, OpenTelemetry, Neo4j, Falco, and KEDA.Conduct hands-on labs using LangChain, Ollama, Prophet, and other AI/ML frameworks.Help participants set up smart workflows for alert classification and routing using open-source stacks.Prepare learners to handle security, threat detection, and runtime anomaly classification using LLMs.Provide post-training support and mentorship when necessary.
Skills
Kubernetes: Minikube, Helm, kubectl, HPA, KEDA
Observability & Monitoring: Prometheus, Grafana, OpenTelemetry, ELK Stack, FluentBit
AI/ML: Python, scikit-learn, Prophet, LangChain, Ollama (LLMs)
Security Tools: Falco, KubeArmor, Sysdig Secure
Dev Tools: Docker, VSCode, Jupyter Notebooks
LLMs & Automation: LangChain, Neo4j, GPT-based explanation tools, Slack Webhooks
QCS Dc Labs
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