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
You are the person a customer calls when their Elasticsearch platform is the problem, or when they need one designed properly the first time.
That means you decide the shape of a cluster and then defend that decision — node topology, shard strategy, data tiers, lifecycle and retention — with the sizing arithmetic to back it up. It also means you can follow a performance problem beyond Elastic itself.
We need someone whose instinct is to look down the stack and sideways to whatever else shares the infrastructure, rather than stopping at the cluster API.
What You Will Be Doing
- Design and build Elasticsearch platforms for customers across self-managed, orchestrated and managed deployments, including air-gapped and regulated environments
- Own sizing and capacity planning as a derivation from workload characteristics — ingest rate, document shape, retention, query concurrency, growth — validated by benchmark rather than estimated from a form
- Run health checks and remediation on production estates, and redesign sharding, mapping and index strategies where the original design no longer holds
- Lead major-version upgrades, snapshot and disaster recovery strategy, and multi-cluster architectures
- Diagnose performance problems across the full stack — Elastic, the JVM, the operating system, storage and network — and across adjacen
📌 Consulting Architect (India)
🏢 Elastic
📍 India