Sr Subject Matter Expert (DFS)

About the role

We are looking for an AI Observability Architect to design and lead the transformation of monitoring and reliability operations from reactive to predictive and self-healing. The role involves architecting AI-driven observability platforms, defining ML/DL model strategy, and enabling automated detection, correlation, and remediation across IT systems.

What you'll do

• Architect an end-to-end AI observability platform unifying logs, metrics, traces, and events into a single observability data store
• Design the strategy for predictive/unsupervised ML & DL models (Isolation Forest, Autoencoders, LSTM) for anomaly detection, degradation prediction
• Define architecture for risk scoring, feature engineering pipelines, and time-window based telemetry aggregation across infra, network, and process signals
• Build the framework for automated alerting and proactive remediation, progressing toward AI-driven and AI-led resolution with reduced human intervention
• Define KPIs/SLOs for critical systems and translate them into monitored signals within the observability platform

What you need

• Machine learning
• Root cause analysis
• Azure
• Python
• Scikit-learn
• TensorFlow
• Any graduate

Good to have

• PyTorch
• Databricks
• Spark