ServiceNow is looking to transform how users interact with and discover information on their platform by enhancing employee and customer-facing search capabilities with AI-powered search, focusing on relevance, accuracy, personalization, and AI-enhanced discovery.
Requirements
- Deep understanding of search ranking techniques and semantic techniques (vector search, transformers, embeddings).
- Proven experience building RAG pipelines, with knowledge of different RAG variants (e.g., Fusion, Condenser, Retrieval with Memory Augmentation, Multi-hop RAG).
- Deep knowledge of AI/ML frameworks and search technologies (e.g., Moveworks, Glean, Elasticsearch, Coveo), particularly focused on data indexing, context awareness, and relevance ranking.
- Hands-on experience with search engines such as Elasticsearch, Apache Solr, Vespa, Pinecone, Weaviate, FAISS, Qdrant, etc.
- Proficiency in ServiceNow AI Search features and architecture — or demonstrable experience with similar platforms.
- Expertise in NLP, LLMs, embedding generation, and retrieval quality optimization.
- Strong programming skills in Python, Java, or JavaScript.
Responsibilities
- Design and Architect Enterprise Search Systems for internal tools and customer-facing experiences, ensuring scalability, performance, and high availability.
- Own the relevance roadmap: continually improve precision, recall, and user satisfaction via tuning, personalization, and ranking strategies.
- Drive AI-powered search capabilities including Retrieval-Augmented Generation (RAG), embedding-based retrieval, semantic search, and hybrid techniques.
- Integrate structured and unstructured data sources across the enterprise for unified search.
- Partner with ML/NLP teams to develop and fine-tune search ranking algorithms, LLM-based query understanding, entity recognition, and document summarization.
- Lead adoption and evolution of ServiceNow AI Search features, including Search Configuration, Search Sources, and Vector Search modules.
- Create reusable search patterns, accelerators, and frameworks for faster onboarding of new applications or data domains.
Other
- 15+ years of experience in search architecture, information retrieval, or AI/ML applied to enterprise or consumer search platforms.
- Experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel) in production settings.
- Understanding of ServiceNow’s architecture, Common Service Data Model (CSDM), and Now Platform data constructs.
- Prior experience implementing search in enterprise ecosystems, such as ITSM, HR, Security, or Customer Support domains.
- Familiarity with observability and metrics for search quality.
