Principal Search Consulting Architect - Elastic

What is the Role

As a Principal Search Architect, you will serve as the elite technical authority and visionary leader helping our largest enterprise customers unlock the full potential of Elasticsearch. Acting as a strategic, trusted advisor to CTOs and Enterprise Architecture teams, you will design, govern, and scale massive, complex Elasticsearch cluster topologies that transform application search performance, data retrieval infrastructure, and AI-powered semantic search capabilities.

You will bridge the gap between business strategy and cutting-edge distributed systems engineering, collaborating directly with Elastic’s global Professional Services leadership, Core Engineering, Product Management, and Sales executives.

What You Will Be Doing

• Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures.
• Cluster Governance & Design: Lead technical strategy for high-stakes engagements, including node blueprinting, capacity planning, shard strategy, ILM, and CCR/CCS.
• Advanced Vector Search & AI Engineering: Design and operationalize semantic search architectures using kNN, ANN, ELSER, hybrid retrieval, and RAG pipelines.
• Performance Tuning & Optimization: Profile and tune distributed search/indexing for ultra-high-QPS environments, optimizing Lucene segment merging, caching, and heap/GC configurations.
• High-Throughput Indexing: Architect robust ingestion strategies for petabyte-scale throughput.
• Cross-Functional Influence: Collaborate with Product and Engineering to influence the Elasticsearch roadmap and drive feature enhancements.
• Community & IP Development: Publish global best practices, reference architectures, and reusable solution patterns.
• Culture of Excellence: Mentor senior engineers and cultivate deep mastery of Elasticsearch internals.

What You Bring

• 8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with deep expertise in Elasticsearch at scale.
• Elasticsearch Internals Mastery: Comprehensive understanding of distributed systems theory, consensus protocols, node roles, and Lucene indexing mechanics.
• AI-Powered Search Expertise: Proven track record of deploying production-grade semantic search solutions using ML nodes and vector fields.
• Cloud-Native Infrastructure: Advanced knowledge of AWS, Azure, or GCP using Docker and Terraform.
• Polyglot Coding: Proficiency in Java, Python, or Go with experience using official client libraries and custom plugins.
• Elite Communication: Exceptional storytelling skills with experience aligning technical roadmaps with business strategy.
• Education: Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field (or equivalent experience).
• Global Mindset: Ability to work across distributed teams and travel for strategic engagements.