Agentic Search Infrastructure Engineer - Moveworks

Moveworks; Mountain View (CA); Híbrido; USD 100 000 - 130 000; Tempo integral

Resumo da oferta

Moveworks in Mountain View, California, is seeking an Agentic Search Infrastructure Engineer to develop a composable search infrastructure for agents. This role involves building a robust search platform, optimizing indexing technology, and ensuring reliable search capabilities through collaboration across various engineering teams.

Candidates should possess a BS or MS in Computer Science and at least one year of hands-on experience with search technologies like Elasticsearch. The emphasis is on a collaborative, in-person work environment.

Qualificações

• 1+ years of full-time industry experience in search technologies.
• Hands-on experience with search platforms like Elasticsearch or OpenSearch.
• Excited to work collaboratively in an in-person team.

Responsabilidades

• Build and own the infrastructural substrate beneath the agentic search platform.
• Design and run high-throughput ingestion and enrichment pipelines.
• Contribute to a knowledge graph linking disparate resources.

Conhecimentos

Experience with search technologies

Proficiency in Lucene, Solr, Elasticsearch, or OpenSearch

Collaboration skills

Formação académica

BS or MS in Computer Science

PhD (preferred)

Ferramentas

Vector databases

Descrição da oferta de emprego

Agentic Search Infrastructure Engineer - Moveworks

Other Mountain View, CALIFORNIA, United States Full-time

Job Description

Contribute to the org-wide shift from product-specific search solutions to a composable, agent-native infrastructure foundation that agents and applications build on to locate, search, discover, and recommend resources across heterogeneous enterprise data.

• 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.

This is a highly collaborative, in-person role, working cross-functionally with Search Ranking, ML, and Platform engineering teams to deliver robust, production-grade agentic search capabilities.

Qualifications

• 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.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [e-mail] for assistance.

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