About the company
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
Responsibilities
- Lead the design, development, and operation of critical search infrastructure components, including indexing systems, ingestion pipelines, metadata enrichment frameworks, and retrieval foundations that support a growing ecosystem of AI agents.
- Drive technical strategy and architectural decisions across multiple search infrastructure domains, ensuring the platform scales to support future agent use cases and expanding enterprise datasets.
- Serve as the technical authority for the end-to-end search lifecycle, from content ingestion through retrieval and ranking.
- Design and operate large-scale hybrid indexing architectures that combine sparse retrieval, dense vector search, semantic retrieval, and emerging indexing approaches.
- Establish clean abstractions and interfaces that allow downstream ranking systems and AI agents to leverage search capabilities consistently across multiple retrieval paradigms.
- Drive innovations that improve search quality, latency, scalability, and cost efficiency across billions of indexed entities.
- Architect high-throughput ingestion and enrichment pipelines that transform enterprise content into rich, permission-aware representations optimized for agent consumption.
- Define strategies for content parsing, chunking, embedding generation, entity extraction, metadata enrichment, and access control enforcement.
- Ensure consistency between index-time representations and query-time retrieval mechanisms to provide reliable foundations for agent reasoning.
- Lead the evolution of indexing and retrieval systems across diverse enterprise content types, including text, structured data, images, diagrams, audio, and video.
- Develop unified frameworks that enable agents to discover and reason across modalities through a consistent retrieval experience.
- Partner with ML and AI teams to bring emerging multi-modal capabilities into production.
- Contribute to the design and evolution of enterprise knowledge graph capabilities that connect people, content, tickets, documents, conversations, and business entities.
- Lead initiatives that improve entity resolution, relationship extraction, and knowledge graph enrichment.
Requirements
- Experience in search infrastructure, indexing, and retrieval systems.
- Strong background in distributed systems and large-scale data processing.
- Experience with hybrid indexing architectures (sparse, dense, semantic).
- Knowledge of multi-modal search and content types.
- Experience with enterprise knowledge graphs and entity resolution.
- Ability to lead technical strategy and architectural decisions.
- Experience partnering with ML and AI teams.
Conditions
- Full-time
- Employee Type: Regular
- Region: AMS - North America and Canada
- Work Persona: Required in Office