Consulting Architect - Search

As a Senior Search Consulting Architect, you will serve as a hands-on technical authority and trusted implementation leader helping enterprise customers unlock the full potential of Elasticsearch. You will design, optimize, and scale complex Elasticsearch cluster topologies, bridging business requirements and distributed systems engineering.

• Translate business and functional requirements into resilient, scalable search architectures built on distributed Elasticsearch environments.
• 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).
• Deploy and operationalize semantic search implementations using Elasticsearch's native vector capabilities, including kNN, ELSER, hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.
• Profile, benchmark, and tune distributed search and indexing performance to meet SLAs, optimizing JVM heap, garbage collection, caching layers, and Apache Lucene segment merging.
• Build robust ingestion pipelines and bulk indexing strategies for high-volume workloads.
• Serve as lead technical consultant during client engagements, leading kickoff meetings, architectural reviews, and hands-on migration efforts.
• Identify edge cases and architectural hurdles, sharing feedback with Product Management and Core Support.
• Document implementation patterns, contribute to standard delivery frameworks, and mentor team members.

• 5+ years as a Solutions Architect, Lead Engineer, or Senior Systems Consultant with deep technical expertise in Elasticsearch in production environments.
• Solid understanding of distributed systems principles as applied to Elasticsearch, including node roles, Apache Lucene indexing mechanics, and cluster state management.
• Proven track record implementing semantic search solutions using Elasticsearch's native ML nodes, dense/sparse vector fields, and modern NLP framework integrations.
• Practical experience deploying Elasticsearch on AWS, Azure, or GCP using Docker, Kubernetes, or Terraform.
• Proficiency in at least one modern programming language (e.g., Java, Python, Go) with experience using official Elasticsearch client libraries.
• Strong presentation and technical writing skills.
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience.
• Comfortable working across distributed teams and traveling to customer sites as required.

Base salary range: $133,100—$210,600 USD; in select locations (Seattle WA, Los Angeles CA, San Francisco Bay Area CA, New York City Metro Area): $159,900—$252,900 USD. Eligible for Elastic's stock program. Company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings. Additional benefits include health coverage, flexible locations and schedules, generous vacation days, up to $2000 match for financial donations and service, up to 40 hours for volunteer projects, and minimum 16 weeks of parental leave.

Apply via the provided link.