Senior Staff Agentic Search Infrastructure

Responsibilities

• Lead the design, development, and operation of search infrastructure components including indexing systems, ingestion pipelines, metadata enrichment frameworks, and retrieval foundations.
• Drive technical strategy and architectural decisions for scalable search infrastructure supporting AI agents and large enterprise datasets.
• Design and operate hybrid indexing architectures combining sparse retrieval, dense vector search, semantic retrieval, and emerging indexing approaches.
• Build high-throughput ingestion and enrichment pipelines with content parsing, chunking, embedding generation, entity extraction, metadata enrichment, and access control enforcement.
• Lead multimodal indexing and retrieval across text, structured data, images, diagrams, audio, and video.
• Contribute to enterprise knowledge graph capabilities, entity resolution, relationship modeling, and contextual understanding.
• Own search latency, indexing throughput, retrieval quality, infrastructure efficiency, and cluster health metrics.
• Drive observability, capacity planning, resiliency engineering, lifecycle management, and infrastructure cost optimization.
• Provide technical leadership and mentorship while influencing roadmap and architecture across multiple engineering teams.
• Lead multi-quarter initiatives spanning Search Infrastructure, Ranking, ML, Platform, and AI teams.

Requirements

• BS or MS in Computer Science or a related technical field; a PhD is preferred.
• 8–12+ years of industry experience building large-scale distributed systems, search platforms, or data infrastructure.
• Deep hands-on experience with search technologies such as Lucene, Elasticsearch, OpenSearch, Solr, or comparable retrieval systems.
• Strong experience designing and operating distributed systems at scale, including storage, indexing, serving, and data processing infrastructure.
• Experience building production systems using vector search, embeddings, retrieval systems, or AI-driven search capabilities.
• Proven ability to lead complex technical initiatives across teams and influence architecture beyond an individual team’s scope.
• Experience with information retrieval, ranking systems, recommendation systems, or AI-powered search platforms is preferred.
• Experience with knowledge graphs, entity resolution systems, or enterprise data modeling is preferred.
• Familiarity with dense retrieval, RAG architectures, hybrid search, and semantic indexing is preferred.
• Experience operating large-scale search clusters and performance-sensitive distributed infrastructure is preferred.
• Experience working with ML or AI platform teams to productionize intelligent retrieval systems is preferred.
• Strong communication, collaboration, technical depth, pragmatic delivery, and operational excellence are expected.

Benefits

• Base pay is $190,900–$334,100, plus equity when applicable, variable/incentive compensation, and benefits.
• Benefits include health plans, flexible spending accounts, a 401(k) plan with company match, ESPP, matching donations, flexible time away, and family leave programs.
• The role has a required-in-office work persona and is part of an in-person engineering culture.
• The position is a regular employee role in the AMS–North America and Canada region.