Elastic

1 month ago

Principal Search Consulting Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead as the trusted technical authority for massive Elasticsearch deployments, shaping enterprise-scale search architectures, AI-powered vector search, and high-throughput indexing. Drive governance, migrations, and regional standards while mentoring senior engineers and aligning technical roadmaps with business goals. Collaborate across Professional Services, Core Engineering, Product, and Sales to influence Elasticsearch roadmaps and share best practices worldwide.

Location: Brazil

Workplace: Onsite

Employment Type: Full time

Job Function: Consulting & Advisory

Seniority: Sr. Manager level

Key Responsibilities

•Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures built on distributed Elasticsearch environments.
•Cluster Governance & Design: Lead technical strategy and design authority for high-stakes customer engagements, including node blueprinting, capacity planning, custom mappings, ILM, and cross-cluster replication.
•Advanced Vector Search & AI Engineering: Design semantic search architectures using native vector capabilities (kNN, ANN, ELSER), hybrid retrieval, and RAG pipelines.
•Performance Tuning & Optimization: Profile, benchmark, and tune distributed search/indexing for ultra-high-QPS with sub-second SLAs, including Lucene optimizations.
•High-Throughput Indexing: Architect distributed ingestion strategies for petabyte-scale throughput and optimized cluster state performance.

Key Requirements

•8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with deep Elasticsearch expertise at massive scale
•Elasticsearch Internals Mastery: distributed systems theory, consensus, node roles, Lucene indexing, cluster state management
•AI-Powered Search Expertise: production-grade semantic search using Elasticsearch native ML nodes, dense/sparse vector fields, and NLP/LLM integrations
•Cloud-Native Infrastructure: orchestrating massive Elasticsearch workloads across AWS, Azure, GCP with Docker and Terraform
•Polyglot Coding: proficiency in Java, Python, Go with Elasticsearch client libraries and plugin development

Experience:8+ yearsEnterprise softwareCloudSearch

Education:Bachelor's

Skills:CommunicationLeadershipPresentation

Languages:English

Tech Stack:JavaPythonGoElasticsearchDockerTerraformAWSAzureGCPLuceneKNNANNELSERRAGCCS

Company Brief

Elastic

Builds the Elastic Stack (Elasticsearch, Kibana, Beats, Logstash) and provides search, observability, and security solutions that enable organizations to search, analyze, and protect data in real time across applications, infrastructure, and enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Amsterdam, Netherlands

Founded: 2012

Website LinkedIn

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Elastic

1 month ago

Principal Search Consulting Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Brazil

Workplace: Onsite

Employment Type: Full time

Job Function: Consulting & Advisory

Seniority: Sr. Manager level

Key Responsibilities

•Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures built on distributed Elasticsearch environments.
•Cluster Governance & Design: Lead technical strategy and design authority for high-stakes customer engagements, including node blueprinting, capacity planning, custom mappings, ILM, and cross-cluster replication.
•Advanced Vector Search & AI Engineering: Design semantic search architectures using native vector capabilities (kNN, ANN, ELSER), hybrid retrieval, and RAG pipelines.
•Performance Tuning & Optimization: Profile, benchmark, and tune distributed search/indexing for ultra-high-QPS with sub-second SLAs, including Lucene optimizations.
•High-Throughput Indexing: Architect distributed ingestion strategies for petabyte-scale throughput and optimized cluster state performance.

Key Requirements

•8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with deep Elasticsearch expertise at massive scale
•Elasticsearch Internals Mastery: distributed systems theory, consensus, node roles, Lucene indexing, cluster state management
•AI-Powered Search Expertise: production-grade semantic search using Elasticsearch native ML nodes, dense/sparse vector fields, and NLP/LLM integrations
•Cloud-Native Infrastructure: orchestrating massive Elasticsearch workloads across AWS, Azure, GCP with Docker and Terraform
•Polyglot Coding: proficiency in Java, Python, Go with Elasticsearch client libraries and plugin development

Experience:8+ yearsEnterprise softwareCloudSearch

Education:Bachelor's

Skills:CommunicationLeadershipPresentation

Languages:English

Tech Stack:JavaPythonGoElasticsearchDockerTerraformAWSAzureGCPLuceneKNNANNELSERRAGCCS

Company Brief

Elastic

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Amsterdam, Netherlands

Founded: 2012

Website LinkedIn