Relevance Engineer – Enterprise Search & AI Hybrid
Core
Architect and optimize hybrid retrieval systems and relevance models to power intelligent knowledge discovery for employees and customers.
Role type
Senior IC relevance engineer (enterprise search & AI hybrid)
Builds
Intelligent, context-aware search experiences integrating traditional IR with Generative AI and RAG pipelines
Domain
Enterprise search, information retrieval, Generative AI, RAG
Deliverable
production ML models
Required skills
Elasticsearch production operations, search relevance tuning (ranking, scoring, analyzers), Python/Java, large-scale data processing, query analytics, experimentation frameworks
Preferred skills
Generative AI/LLM integration, RAG frameworks, vector search, hybrid search (keyword + vector), evaluation metrics (NDCG, MRR, A/B testing)
Technologies
Elasticsearch, Python, Java, RAG pipelines
Responsibilities
Architect and optimize hybrid retrieval systems leveraging semantic embeddings and re-ranking models; Develop and tune relevance models using query analytics and behavioral signals; Integrate Generative AI capabilities with traditional information retrieval systems; Implement and optimize RAG pipelines combining structured and unstructured data; Partner with AI engineers and product stakeholders to define measurable improvements in search quality
Seniority
Senior, hands-on IC