This role pays less than
59%
of similar roles. Most pay
$174,600–$227,862
— the shaded band above.
At the midpoint, this role pays about
$206k
versus about
$201k
for comparable roles.
Based on 240 similar postings.
Employer
About Elastic
Elastic is the company behind Elasticsearch and the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash). It sells search, observability, and security products built on that search engine, primarily through its Elastic Cloud managed service.
Elastic currently has
240 open roles
on FindRole.
Listed pay typically runs
$133,100–$210,600
across 91 roles with salary data.
As a Principal Search Consulting Architect, you will serve as a technical authority and visionary leader helping enterprise customers unlock the full potential of Elasticsearch. You will act as a strategic advisor to executive teams, designing and governing complex cluster topologies that improve data retrieval infrastructure and AI-powered semantic search capabilities. Your daily responsibilities include translating business requirements into resilient architectures, managing cluster governance, performing performance tuning for high-QPS environments, and developing advanced vector search pipelines using kNN, ELSER, and RAG. You will utilize technologies including Elasticsearch, Apache Lucene, Docker, Terraform, and programming languages like Java, Python, and Go. This role solves critical challenges in distributed systems engineering by building scalable infrastructure for large-scale data indexing, while also influencing the product roadmap and establishing global best practices for search and AI integration.
Translate complex business requirements into resilient, large-scale enterprise retrieval architectures using distributed Elasticsearch environments.
Lead technical strategy for high-stakes engagements including node blueprinting, capacity planning, and shard management.
Design and operationalize advanced vector search architectures featuring kNN, ELSER, and RAG pipelines.
Profile and tune distributed search performance to meet sub-second SLAs in high-QPS environments.
Architect robust ingestion strategies for petabyte-scale data while optimizing cluster state and thread pools.
Influence the Elasticsearch product roadmap by collaborating with engineering teams to address enterprise requirements.
Develop and publish global best practices, reference architectures, and reusable solution patterns for the community.
Mentor internal staff and external clients to foster a culture of technical excellence in Elasticsearch.
What we're looking for
Must have 8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with deep expertise in Elasticsearch at scale.
Must possess comprehensive knowledge of distributed systems theory and Elasticsearch internals including Lucene mechanics and cluster state management.
Must have a proven track record of deploying production-grade semantic search solutions using vector fields and LLM orchestration tools.
Must have advanced knowledge of orchestrating large-scale workloads across AWS, Azure, or GCP using Docker and Terraform.
Must be proficient in multiple programming languages such as Java, Python, or Go with experience in Elasticsearch client libraries.
Must possess exceptional communication skills to present technical roadmaps to executive stakeholders.
Must have a Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related quantitative field (or equivalent experience).
Must be able to work across distributed global teams and travel to client sites as required.
Agentic AI
Distributed Systems
Microservices
APIs
Platform Engineering
Kafka
Spark
Data Management
Real-time Processing
System Architecture
Observability
Scalability
Data Governance
Artificial Intelligence
Generative AI
Agentic AI
Microservices
APIs
Data Platforms
Event-Driven Architecture
C4 Model
Agile
SAFe
Performance Engineering