Elastic - Principal Search Consulting Architect
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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. • 8+ years • Elasticsearch • 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. • Elasticsearch Internals Mastery: • 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. • AI-Powered Search Expertise: • Cloud-Native Infrastructure: Advanced knowledge of orchestrating massive Elasticsearch workloads across cloud platforms (AWS, Azure, GCP) using cloud-native patterns, Docker, and Terraform. • Cloud-Native Infrastructure: • 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. • Polyglot Coding: • 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. • Elite Communication: • Education: Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related quantitative field, or equivalent deep industry experience. • Education: • Global Mindset: Comfortable working effectively across highly distributed, global teams and traveling to client sites as required for strategic architectural engagements. • Global Mindset: • Additional Information - We Take Care of Our People: • As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do. • We strive to have parity of benefits across regions, and while regulations differ from place to place, we believe taking care of our people is the right thing to do. • Competitive pay based on the work you do here and not your previous salary • Health coverage for you and your family in many locations • Ability to craft your calendar with flexible locations and schedules for many roles • Generous number of vacation days each year • Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service • Up to 40 hours each year to use toward volunteer projects you love • Embracing parenthood with a minimum of 16 weeks of parental leave
Responsibilities
• Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures built natively on distributed Elasticsearch environments. • Elasticsearch Core Architecture: • 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). • Cluster Governance & Design: • Advanced Vector Search & AI Engineering: Design and operationalize cutting-edge semantic search architectures utilizing 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. • Advanced Vector Search & AI Engineering: • 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. • Performance Tuning & Optimization: • 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. • High-Throughput Indexing: • Cross-Functional Influence: Collaborate cross-functionally with Elastic Product Management and Core Engineering to influence the Elasticsearch codebase roadmap, surface edge-case bugs, and drive feature enhancement requests based on enterprise field realities. • Cross-Functional Influence: • Culture of Excellence: Drive internal enablement initiatives, mentor senior engineers, and cultivate a culture of continuous technical excellence and deep mastery of Elasticsearch internals. • Culture of Excellence:
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