This role pays less than
66%
of similar roles. Most pay
$162,150–$233,125
— the shaded band above.
At the midpoint, this role pays about
$172k
versus about
$198k
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 Senior Consulting Architect - Search, you will serve as a technical authority and implementation leader helping enterprise customers leverage Elasticsearch. You will design, optimize, and scale complex cluster topologies to improve search performance, data retrieval infrastructure, and AI-powered semantic search capabilities. Your daily responsibilities include translating business requirements into resilient architectures, performing capacity planning, managing index lifecycles, and building high-throughput ingestion pipelines. You will also deploy advanced vector search features like kNN and RAG pipelines while providing technical mentorship and feedback to product teams. The role requires expertise in Elasticsearch internals, Apache Lucene, and cloud-native infrastructure using Docker, Kubernetes, or Terraform. Candidates must be proficient in at least one programming language such as Java, Python, or Go to manage distributed systems and solve complex data retrieval challenges for enterprise clients.
Translate business requirements into scalable and resilient search architectures on distributed Elasticsearch environments.
Design cluster topologies including capacity planning, custom mappings, shard strategies, and Index Lifecycle Management.
Deploy and operationalize semantic search features using vector capabilities, ELSER, and RAG pipelines.
Profile and tune distributed search performance to optimize JVM heap, caching, and Lucene segment merging.
Build robust ingestion pipelines and bulk indexing strategies for high-volume data workloads.
Lead technical consultations, architectural reviews, and hands-on migration efforts for enterprise customers.
Identify and report field bugs and architectural hurdles to Product Management and Core Support teams.
Mentor internal staff and document implementation patterns to improve standard delivery frameworks.
What we're looking for
5+ years of experience as a Solutions Architect, Lead Engineer, or Senior Systems Consultant with deep expertise in production Elasticsearch environments.
Deep understanding of distributed systems principles, including Apache Lucene indexing mechanics and Elasticsearch cluster state management.
Proven track record of implementing semantic search solutions using vector fields, ML nodes, and RAG pipelines.
Practical experience managing Elasticsearch workloads on public cloud platforms (AWS, Azure, GCP) using Docker, Kubernetes, or Terraform.
Proficiency in at least one modern programming language such as Java, Python, or Go with experience using official client libraries.
Strong technical communication skills for presenting complex architectural choices to developer teams and executive leadership.
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical industry experience.