Design and maintain scalable data pipelines and storage systems Productionize LLM- and agent-based workflows Build and maintain feature stores, vector/embedding stores, and core data assets Develop and manage end-to-end traditional ML pipelines Implement data quality checks, drift detection, and automated retraining processes Optimize cost, latency, and performance across all AI/ML infrastructure Collaborate to deliver production-ready ML and AI systems Ensure AI/ML systems meet governance, security, and compliance requirements Mentor teams and drive innovation across ML engineering practices Participate in team meetings and contribute to project planning