Aiops, Mlops Operations Associate Manager

**Overview****We Are PepsiCo**Join PepsiCo and Dare for Better We are the perfect place for curious people, thinkers and change agents. From leadership to front lines, we're excited about the future and working together to make the world a better place.Being part of PepsiCo means being part of one of the largest food and beverage companies in the world, with our iconic brands consumed more than a billion times a day in more than 200 countries.Our product portfolio, which includes 22 of the world's most iconic brands, such as Sabritas, Gamesa, Quaker, Pepsi, Gatorade and Sonrics, has been a part of Mexican homes for more than 116 years.A career at PepsiCo means working in a culture where all people are welcome. Here, you can dare to be you. No matter who you are, where you're from, or who you love, you can always influence the people around you and make a positive impact in the world.**Know more**:- PepsiCoJobs**Join PepsiCo, dare for better.****Responsibilities****The Opportunity****Your Impact**As **AIOps, MLOps Operations Associate Manager (IBP)** your scope would consist of- 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****Who Are We Looking For?****Required**:- 5+ years of technology work experience in a global organization, preferably in CPG or a similar industry. - 5+ years of experience in the Data & Analytics field, with exposure to AI/ML operations and cloud-based platforms. 5+ years of experience working within cross-functional IT or data operations teams- Strong understanding of AIOps and MLOps lifecycle, from model development to deployment and monitoring.- Proficiency in cloud platforms (AWS, Azure, GCP) for AI/ML workloads, including services like Azure ML, AWS SageMaker, or Google AI Platform.- Experience in model deployment (MLflow, Kubeflow) and using monitoring tools (Prometheus, Grafana) for model health and performance.- Strong background in automating pipelines using CI/CD tools (Jenkins, GitLab) and container orchestration (Docker, Kubernetes).**Nice to have**:- Experience with drift detection tools (Evidently.ai, Alibi Detect) for proactive model monitoring.- Exposure to working in multi-cloud environments (Azure, AWS, GCP) for AI/ML deployment and integration.- E