Associate Manager, D&AI AIOps, MLOps Operations, IBP

Responsibilities

• Support the implementation of AIOps strategies for automating IT operations using Azure Monitor, Azure Log Analytics, and AI-driven alerting.
• Assist in deploying Azure-based observability solutions (Azure Monitor, Application Insights, Azure Synapse for log analytics, and Azure Data Explorer) to enhance real-time system performance monitoring.
• Enable AI-driven anomaly detection and root cause analysis (RCA) by collaborating with data science teams using Azure Machine Learning (Azure ML) and AI-powered log analytics.
• Contribute to developing self-healing and auto-remediation mechanisms using Azure Logic Apps, Azure Functions, and Power Automate to proactively resolve system issues.
• Support ML lifecycle automation using Azure ML, Azure DevOps, and Azure Pipelines for CI / CD of ML models.
• Assist in deploying scalable ML models with Azure Kubernetes Service (AKS), Azure Machine Learning Compute, and Azure Container Instances.
• Automate feature engineering, model versioning, and drift detection using Azure ML Pipelines and MLflow.
• Optimize ML workflows with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for data preparation and ETL / ELT automation.
• Implement basic monitoring and explainability for ML models using Azure Responsible AI Dashboard and InterpretML.
• Collaborate with Data Science, DevOps, CloudOps, and SRE teams to align AIOps / MLOps strategies with enterprise IT goals.
• Work closely with business stakeholders and IT leadership to implement AI-driven insights and automation to enhance operational decision-making.
• Track and report AI / ML operational KPIs, such as model accuracy, latency, and infrastructure efficiency.
• Assist in coordinating with cross-functional teams to maintain system performance and ensure operational resilience.
• Support the implementation of AI ethics, bias mitigation, and responsible AI practices using Azure Responsible AI Toolkits.
• Ensure adherence to Azure Information Protection (AIP), Role-Based Access Control (RBAC), and data security policies.
• Assist in developing risk management strategies for AI-driven operational automation in Azure environments.
• Prepare and present program updates, risk assessments, and AIOps / MLOps maturity progress to stakeholders as needed.
• Support efforts to attract and build a diverse, high-performing team to meet current and future business objectives.
• Help remove barriers to agility and enable the team to adapt quickly to shifting priorities without losing productivity.
• Contribute to developing the appropriate organizational structure, resource plans, and culture to support business goals.
• Leverage technical and operational expertise in cloud and high-performance computing to understand business requirements and earn trust with stakeholders.

Qualifications

Skills Required

Ml, Azure, Gcp, Customer Satisfaction, Ai, Aws, Data Analytics, Communication