Consulting Architect - Platform
Elastic · Posted Sep 17
Search, observability, security, and analytics platform services
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About the role
Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale, and the Elastic Search AI Platform is used by more than 50% of the Fortune 500. This Consulting Architect - Platform role is for the person a customer calls when their Elasticsearch platform is the problem, or when they need one designed properly the first time. The architect will design and build Elasticsearch platforms across self-managed, orchestrated and managed deployments, own sizing and capacity planning, lead upgrades and disaster recovery strategy, and diagnose performance problems across the full stack.
What you will do
- 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 adjacent systems in the data path
- Work directly with customer architects, platform owners and engineering leadership; run discovery, present designs, and own the technical outcome of an engagement end to end
- Build reusable tooling, automation and IP that makes the next engagement faster, including AI-assisted tooling for diagnosis, configuration and reporting
- Mentor other consultants and contribute to the GCC's technical practice
Skills used in this role
What the employer is looking for
- 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.
- We are not looking for someone who will learn Elastic on the job.
- 8+ years hands-on with the Elastic Stack, substantially on cluster and platform work rather than dashboarding or pipeline authoring
- Shard strategy you can derive, not recite — how you arrived at a shard count and size for a given workload, what you traded off, and what you got wrong the first time
- Index and mapping design, and why those choices drive cluster performance
- Lifecycle and retention across data tiers, including the cost and latency implications of each
- Snapshot, restore and disaster recovery designed and executed, not just configured
- Major-version upgrades in production — the sequencing, the breaking changes, the rollback position
- More than one deployment model: self-managed plus at least one managed or orchestrated option
- Cluster stability and performance troubleshooting — heap and garbage collection, circuit breakers, thread pool rejections, shard allocation, expensive queries
- Elastic Certified Engineer, or the demonstrable knowledge to obtain it within your first quarter
- Strong Linux and operating system fundamentals, with solid grounding in storage and networking
- A working understanding of how infrastructure conditions translate into Elastic symptoms, and how infrastructure choices constrain what a deployment can do
- Experience troubleshooting on shared infrastructure, where the cause of your problem is another workload's behaviour and resolving it means engaging the team that owns it
Benefits and support
- Competitive pay based on the work you do here and not your previous salary
- Health coverage for you and your family in many locations
- Ability to craft your calendar with flexible locations and schedules for many roles
- Generous number of vacation days each year
- Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
- Up to 40 hours each year to use toward volunteer projects you love
- Embracing parenthood with minimum of 16 weeks of parental leave
About Elastic
Elastic is a search AI company that builds self-managed and SaaS offerings for search, logging, security, observability, and analytics. Powered by the Elasticsearch platform, the company helps thousands of organizations worldwide transform massive volumes of data into actionable insights and real-time answers. Its modern search solutions are widely integrated across enterprise tech ecosystems to support advanced AI applications and automated security workloads.
- Industry
- Software
- Company size
- 5001-10000 employees
- Founded
- 2012
- Location
- Mountain View, California, USA
- Funding stage
- Public Company
Funding
Public Company · $162M raised
- 2012-11-01Series A$10M
- 2013-03-01Series B$24M
- 2014-06-05Series C$70M
Leadership
Chief Executive Officer
Founder and Chief Technology Officer
Chief Financial Officer
Recent coverage
Business Wire
Elastic N.V. Announces Organizational Restructuring and Leadership Changes2026-06-25
Business Wire
Elastic Names Navam Welihinda Chief Financial Officer2025-02-27
Elastic Investor Relations
Elastic Reports Strong Fourth Quarter and Fiscal 2025 Financial Results2025-06-04