Consulting Architect - Search

Role details

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role As a Senior Search Consulting Architect, you will serve as a hands-on technical authority and trusted implementation leader helping our enterprise customers unlock the full potential of Elasticsearch. Working directly with customer engineering teams and technical leadership, you will design, optimize, and scale 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 requirements and distributed systems engineering, collaborating closely with internal Services Delivery leads, Sales Engineers, and customer architects. In this high-impact role, you will lead critical cluster deployments, drive performance tuning engagements, and mentor technical staff to ensure long-term operational success for key accounts. What You Will Do Elasticsearch Core Architecture: Translate business and functional requirements into highly resilient, scalable search architectures built natively on distributed Elasticsearch environments. Cluster Design & Governance: Lead technical execution and node blueprinting for enterprise customer engagements—including capacity planning, custom mappings, shard strategy, Index Lifecycle Management (ILM), and cross-cluster replication (CCR/CCS). Advanced Vector Search & AI Engineering: Deploy and operationalize semantic search implementations utilizing Elasticsearch’s native vector capabilities, including kNN, ELSER, hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines. Performance Tuning & Optimization: Profile, benchmark, and tune distributed search and indexing performance to meet demanding SLAs, optimizing JVM heap, garbage collection, caching layers, and Apache Lucene segment merging. High-Throughput Ingestion: Build robust ingestion pipelines and bulk indexing strategies handling high-volume workloads while optimizing cluster state performance and thread pools. Customer Engagement & Delivery: Serve as the lead technical consultant during client engagements, leading technical kickoff meetings, architectural reviews, and hands-on migration efforts. Field Insights & Feedback: Identify edge cases, bugs, and common architectural hurdles in field deployments, sharing structured feedback with Product Management and Core Support. Internal Mentorship: Document implementation patterns, contribute to standard delivery frameworks, and mentor team members to cultivate a culture of technical excellence. What You Bring 5+ years as a Solutions Architect, Lead Engineer, or Senior Systems Consultant with hands-on, deep technical expertise specifically focused on Elasticsearch in production environments. Elasticsearch Internals: Solid understanding of distributed systems principles as applied to Elasticsearch, including node roles (master, data, ingest, ML), Apache Lucene indexing mechanics, and cluster state management. AI-Powered Search Experience: Proven track record of implementing semantic search solutions using Elasticsearch’s native ML nodes, dense/sparse vector fields, and modern NLP framework integrations. Cloud-Native Infrastructure: Practical experience deploying and managing Elasticsearch workloads on public cloud platforms (AWS, Azure, GCP) using Docker, Kubernetes, or Terraform. Polyglot Coding: Proficiency in at least one modern programming language (e.g., Java, Python, Go) with experience using official Elasticsearch client libraries. Technical Communication: Strong presentation and technical writing skills, with a proven ability to guide developer teams, customer architects, and IT managers through complex technical choices. Education: Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical industry experience. Global Mindset: Comfortable working across distributed teams and traveling to customer sites as required for key project milestones. Compensation for this role is in the form of base salary. This role does not have a variable compensation component. The typical starting salary range for new hires in this role is listed below. 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. These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future. An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs. Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being. The typical starting salary range for this role is: $133,100 - $210,600 USD The