• Architect, design, and implement cloud-native database solutions across relational, NoSQL, and vector database technologies. • Lead database strategy and standards to support AI/ML and LLM workloads, including embeddings, semantic search, and retrieval-augmented generation (RAG). • Design and optimize data models, schemas, indexing strategies, and storage patterns for performance and scalability. • Build and manage vector databases to support similarity search, recommendations, and AI inference pipelines. • Collaborate with AI/ML engineers, application developers, and platform teams to integrate databases into end-to-end systems. • Ensure high availability, disaster recovery, security, and compliance across all database platforms. • Optimize cost, performance, and reliability in cloud environments. • Implement monitoring, alerting, backup, and automation for database operations. • Provide technical leadership, documentation, and best-practice guidance to engineering teams. • Evaluate and recommend new database technologies and cloud services as requirements evolve.