Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

As a Senior Search Consulting Architect, you will serve as a hands-on technical authority and trusted implementation leader helping our enterprise customers unlock the full potential of Elasticsearch. Working directly with customer engineering teams and technical leadership, you will design, optimize, and scale complex Elasticsearch cluster topologies that transform application search performance, data retrieval infrastructure, and AI-powered semantic search capabilities.

You will bridge the gap between business requirements and distributed systems engineering, collaborating closely with internal Services Delivery leads, Sales Engineers, and customer architects. In this high-impact role, you will lead critical cluster deployments, drive performance tuning engagements, and mentor technical staff to ensure long-term operational success for key accounts.

What You Will Do

Elasticsearch Core Architecture: Translate business and functional requirements into highly resilient, scalable search architectures built natively on distributed Elasticsearch environments.
Cluster Design & Governance: Lead technical execution and node blueprinting for enterprise customer engagements—including capacity planning, custom mappings, shard strategy, Index Lifecycle Management (ILM), and cross-cluster replication (CCR/CCS).
Advanced Vector Search & AI Engineering: Deploy and operationalize semantic search implementations utilizing Elasticsearch’s native vector capabilities, including kNN, ELSER, hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.
Performance Tuning & Optimization: Profile, benchmark, and tune distributed search and indexing performance to meet demanding SLAs, optimizing JVM heap, garbage collection, caching layers, and Apache Lucene segment merging.
High-Throughput Ingestion: Build robust ingestion pipelines and bulk indexing strategies handling high-volume workloads while optimizing cluster state performance and thread pools.
Customer Engagement & Delivery: Serve as the lead technical consultant during client engagements, leading technical kickoff meetings, architectural reviews, and hands-on migration efforts.
Field Insights & Feedback: Identify edge cases, bugs, and common architectural hurdles in field deployments, sharing structured feedback with Product Management and Cor

Consulting Architect - Search