- Empowering large-scale customers to implement Elastic Observability for unified visibility across metrics, logs, and traces in complex, distributed environments. - Integrate Elastic’s ingestion, storage, and visualization capabilities to deliver end-to-end observability. Key areas include deploying Elastic APM, log and metric pipelines, Kubernetes monitoring, root cause analysis, SLO/SLA tracking, real-time alerting, and leveraging machine learning for anomaly detection, log categorization, and proactive performance insights. - Enabling enterprise customers to harness the Elasticsearch Relevance Engine (ESRE) alongside large language models (LLMs) to build advanced Retrieval-Augmented Generation (RAG) solutions. - Focus areas include integrating Elasticsearch’s indexing, semantic search, and vector storage capabilities with LLM workflows, optimizing hybrid search (keyword + vector), developing generative AI use cases, and leveraging the Elastic AI Assistant to enhance performance, relevance, and usability across applications.