Lead Research Engineer, Search & Retrieval
Core
Building next-generation search and retrieval systems for agentic AI workflows over large collections of legal, tax, and regulatory content.
Role type
Lead Research Engineer (Search & Retrieval)
Builds
Production-grade retrieval architectures, ingestion pipelines, ranking systems, and agentic retrieval loops.
Domain
Legal, tax, and regulatory technology; Information Retrieval; Agentic AI
Deliverable
production ML models | product features | infrastructure
Required skills
End-to-end delivery of search/retrieval projects, technical leadership of squads, experimental design and evidence rigor, Python software engineering, AWS distributed systems, information retrieval fundamentals (indexing, vector search, RAG), collaboration with applied scientists
Preferred skills
Learning-to-rank, LLM-based ranking/re-ranking, LLM-as-judge evaluation, event-driven architectures (Kafka), ML infrastructure, text-heavy domain experience
Technologies
OpenSearch, Vespa, Elasticsearch, Solr, Lucene, AWS, Python, Kafka, Vector databases
Responsibilities
Own end-to-end delivery of search and retrieval projects, act as technical lead for a squad of 3–5 engineers, partner with applied scientists to productionize models, design and build retrieval architectures and agentic workflows, build evaluation harnesses to discriminate real improvement, diagnose retrieval failures, operate production APIs and backend services, influence architecture decisions across teams
Seniority
Senior, hands-on IC with leadership responsibilities
