Agentic Search Infrastructure Engineer - Moveworks

Job summary

ServiceNow is seeking an Agentic Search Infrastructure Engineer to contribute to the development of a composable, agent-native infrastructure foundation for search solutions. This role involves building and operating hybrid indexing technology, designing high-throughput ingestion and enrichment pipelines, and improving the performance and scalability of search infrastructure. The position requires collaboration with Search Ranking, ML, and Platform engineering teams.

Qualifications

• BS or MS in Computer Science or 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.
• Additional experience in vector databases is an advantage.
• Excited to be part of an in-person team culture, collaborating on-site with colleagues every day.

Responsibilities

• Contribute to the org-wide shift from product-specific search solutions to a composable, agent-native infrastructure foundation.
• Build and own the infrastructural substrate beneath the agentic search platform, spanning the index engine, ingestion and enrichment pipeline, and entity, identity, and feature intelligence.
• Solve the problem of keeping index-time enrichments aligned with what agents expect at query time.
• 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.
• Own the full index lifecycle and expose clean, unified contracts to search primitives and recipes.
• Design and run high-throughput ingestion and enrichment pipelines that produce a multi-representation, permission-aware corpus at index time.
• Orchestrate stages that make content agent-ready, including parsing, chunking, embedding, entity resolution, and access control.
• Build and operate multi-modal indexing across enterprise data, from free text and structured content to diagrams, images, audio, and video.
• Represent each modality so it is retrievable through a unified surface.
• Contribute to a knowledge graph that resolves entities across enterprise data sources.
• Improve the performance, scalability, and observability of search, including query latency, indexing throughput, and cluster health.
• 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.
• Help shape the search roadmap as the platform grows to support new agents, primitives, and recipes.
• Drive reliability and operability across the platform through index lifecycle policies, capacity planning, and cluster scaling strategies.

Skills

Degrees

Relocation