Principal Search Consulting Architect

About the role

Elastic, the Search AI Company, seeks a Principal Search Architect to lead the design, governance, and scaling of massive, complex Elasticsearch cluster topologies for our largest enterprise customers. This role requires a comprehensive understanding of distributed systems theory as applied to Elasticsearch, including consensus protocols, internal node roles, Apache Lucene indexing mechanics, and cluster state management. The ideal candidate will bridge the gap between business strategy and cutting-edge distributed systems engineering, collaborating with Elastic’s global Professional Services leadership, Core Engineering, Product Management, and Sales executives.

Responsibilities

• Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures built natively on distributed Elasticsearch environments.
• Cluster Governance & Design: Lead the overarching technical strategy and design authority for high-stakes customer engagements, from initial node blueprinting and capacity planning to custom mappings, shard strategy, Index Lifecycle Management (ILM), and cross-cluster replication (CCR/CCS).
• Advanced Vector Search & AI Engineering: Design and operationalize cutting-edge semantic search architectures utilizing Elasticsearch’s native ML nodes, dense/sparse vector fields, and integrations with modern NLP frameworks and LLM orchestration tools.
• Performance Tuning & Optimization: Profile, benchmark, and tune distributed search and indexing performance for ultra-high-QPS environments with aggressive sub-second SLAs, optimizing Apache Lucene segment merging, caching layers, and heap/garbage collection configurations.
• High-Throughput Indexing: Architect robust distributed ingestion strategies handling petabyte-scale throughput, optimizing cluster state performance, thread pools, and bulk indexing requests for maximum efficiency.
• Community & IP Development: Capture, formalize, and publish global best practices, reference architectures, and reusable solution patterns across the broader Elasticsearch and open-source engineering communities.
• Culture of Excellence: Drive internal enablement initiatives, mentor senior engineers, and cultivate a culture of continuous technical excellence and deep mastery of Elasticsearch internals.

Requirements

• 8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with recognized, deep technical expertise specifically focused on Elasticsearch at a massive scale.
• Elasticsearch Internals Mastery: Comprehensive understanding of distributed systems theory as it applies to Elasticsearch, including consensus protocols, internal node roles (master, data, ingest, machine learning), Apache Lucene indexing mechanics, and cluster state management.
• AI-Powered Search Expertise: Proven track record of deploying production-grade semantic search solutions using Elasticsearch’s native ML nodes, dense/sparse vector fields, and integrations with modern NLP frameworks and LLM orchestration tools.
• Cloud-Native Infrastructure: Advanced knowledge of orchestrating massive Elasticsearch workloads across cloud platforms (AWS, Azure, GCP) using cloud-native patterns, Docker, and Terraform.
• Polyglot Coding: Strong proficiency in multiple programming languages (e.g., Java, Python, Go) with extensive experience utilizing official Elasticsearch client libraries and building custom plugins.
• Elite Communication: Exceptional presentation and storytelling skills, with verified experience commanding a room of executive stakeholders to align technical Elasticsearch roadmaps with core business strategy.

Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related quantitative field, or equivalent deep industry experience.
• Global Mindset: Comfortable working effectively across highly distributed, global teams and traveling to client sites as required for strategic architectural engagements.

Skills

• Strong proficiency in multiple programming languages (e.g., Java, Python, Go).
• Experience with Elasticsearch client libraries and building custom plugins.
• Knowledge of cloud-native patterns, Docker, and Terraform.
• Experience with Elasticsearch’s native ML nodes, dense/sparse vector fields, and integrations with modern NLP frameworks and LLM orchestration tools.
• Experience with Elasticsearch’s native vector database capabilities, including kNN, Approximate Nearest Neighbor (ANN), ELSER (Elastic Learned Sparse Encoder), hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.
• Experience with Apache Lucene indexing mechanics and cluster state management.
• Experience with distributed systems theory and consensus protocols.
• Experience with Elasticsearch’s internal node roles (master, data, ingest, machine learning).
• Experience with Elasticsearch’s Index Lifecycle Management (ILM) and cross-cluster replication (CCR/CCS).
• Experience with Elasticsearch’s native vector database capabilities, including kNN, Approximate Nearest Neighbor (ANN), ELSER (Elastic Learned Sparse Encoder), hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.
• Experience with Elasticsearch’s native vector database capabilities, including kNN, Approximate Nearest Neighbor (ANN), ELSER (Elastic Learned Sparse Encoder), hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.
• Experience with Elasticsearch’s native vector database capabilities, including kNN, Approximate Nearest Neighbor (ANN), ELSER (Elastic Learned Sparse Encoder), hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.

Benefits

• Competitive pay based on the work you do here and not your previous salary.
• Health coverage for you and your family in many locations.
• Generous number of vacation days each year.
• Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service.
• To use up to 40 hours each year toward volunteer projects you love.
• Embracing parenthood with a minimum of 16 weeks of parental leave.

Pay

The typical starting salary range for new hires in this role is $159,800—$252,800 USD. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below.

Schedule

Flexible locations and schedules for many roles.