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ServiceNow
Posted 121 days agoVerified live 9h ago

Agentic Search Infrastructure Engineer - Moveworks

Brief overview

1400 Terra Bella Avenue, 94043 Mountain View, CALIFORNIA, United StatesIn-person
UndergradOr in progress
1+ yrsMinimum
1,817 H-1B approvalsDept. of Labor
549 green cardsCertified filings
Search technologiesLuceneSolrElasticsearchOpenSearchVector databasesHybrid indexingIndexing at scaleIngestion pipelinesEnrichment pipelinesEntity resolutionAccess controlMulti-modal indexingKnowledge graphQuery latency optimizationIndexing throughputCluster health monitoring

Visa sponsorship history

4 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
1,817H-1B approved
98%approval rate
410new H-1B hires
549PERM certified
$155,650median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
2023461
2024578
2025652
2026126
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
202392
2024150
2025116
2026143
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
2023133
2024147
2025256
202613
Top sponsored roles
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Job description

Summary

ServiceNow is an innovative company focused on automating tasks and enhancing productivity through AI technology. They are seeking an Agentic Search Infrastructure Engineer to build and maintain the foundational infrastructure for agentic search capabilities, ensuring efficient retrieval and recommendation of enterprise data across various formats. This role involves collaboration with multiple teams to deliver high-quality search solutions.

Responsibilities

  • Build and own the infrastructural substrate beneath the agentic search platform, spanning the index engine, the ingestion and enrichment pipeline, and the entity, identity, and feature intelligence that gives content context
  • Solve the hard problem of keeping index-time enrichments aligned with what agents expect at query time, so retrieval, ranking, and reasoning all build on a consistent foundation
  • Build and operate hybrid indexing technology at scale across large clusters, spanning keyword-based sparse-vector indices, embedding-based semantic indices, and emerging semantic-ID indexing driven by next-token prediction
  • Own the full index lifecycle, and expose clean, unified contracts to the search primitives and recipes that agents compose on top of the corpus
  • Design and run high-throughput ingestion and enrichment pipelines that produce a multi-representation, permission-aware corpus at index time
  • Orchestrate the stages that make content agent-ready, including parsing, chunking, embedding, entity resolution, and access control, and evolve them as new agentic use cases emerge
  • Build and operate multi-modal indexing across the full mix of enterprise data, from free text and structured content such as tables to diagrams, images, and audio and video
  • Represent each modality so it is retrievable through a unified surface, letting agents find the right material regardless of its form or source
  • Contribute to a knowledge graph that resolves entities across enterprise data sources, letting agents link disparate resources such as tickets, files, and people through canonical entity relationships
  • Improve the performance, scalability, and observability of search, including query latency, indexing throughput, and cluster health, to deliver low-latency, high-quality agentic search experiences
  • Apply techniques such as vector quantization to balance model quality, retrieval performance, and storage cost
  • Own search infrastructure end to end, from intake and design through rollout and ongoing operations, and help shape the search roadmap as the platform grows to support new agents, primitives, and recipes, including needs not yet anticipated
  • Drive reliability and operability across the platform through index lifecycle policies, capacity planning, and cluster scaling strategies that keep a growing library of reusable search capabilities healthy in production

Skills

  • BS or MS in Computer Science or an equivalent engineering background; PhD is a plus
  • 1+ years of full-time industry experience
  • Hands-on experience with search technologies; proficiency in one or more search technologies such as Lucene, Solr, Elasticsearch, or OpenSearch is required, with additional experience in vector databases being an advantage
  • Excited to be part of an in-person team culture, collaborating on-site with colleagues every day

Qualifications

Must Haves

  • BS or MS in Computer Science or an equivalent engineering background; PhD is a plus
  • 1+ years of full-time industry experience
  • Hands-on experience with search technologies; proficiency in one or more search technologies such as Lucene, Solr, Elasticsearch, or OpenSearch is required, with additional experience in vector databases being an advantage
  • Excited to be part of an in-person team culture, collaborating on-site with colleagues every day

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