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This is a high-leverage leadership role that spans architecture, execution, and org-building, and will shape the direction of our search platform for years to come. We are seeking a Head of Search → engineering leader to architect, scale, and own the core systems that power Ema’s Search platform. This role is especially critical to building and scaling: Core Search Platform; Integrations internally with other application teams; Integrations with partner teams; Open API specs to bring in the data into Ema
Job Responsibility:
Own the technical roadmap for Search at Ema
Set the roadmap for our Data Ingestion Platform – which enables Ema to securely ingest, transform, and index data from documents, spreadsheets, emails, and SaaS systems
Design and scale our Search Platform, enabling structured and unstructured data to flow seamlessly into Ema for search, reasoning, and generation
Own the architecture and implementation of Ema’s Search Index
Drive and collaborate with the LLMOps infrastructure: influence on how 1000s of transforms can be developed by external folks as well
Ensure platform support for diverse data formats (PDFs, spreadsheets, databases, charts, etc.) using PostgreSQL, Elasticsearch, and other relevant tools
Requirements:
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
12+ years of experience in backend systems, lucene, elastic search, vector datastores, infrastructure and scale
Knowledge of indexing strategies, inverted indexes, sharding/replication, and managing large document corpora
Expertise in ranking algorithms (BM25, vector-based, hybrid)
Familiarity with relevance tuning, query understanding, and search result evaluation
Proficiency with metrics (precision, recall, NDCG, MRR, etc.)
Proven experience in building the search infrastructure and scaling real-time systems on the search engine
Deep understanding of knowledge search
Deep expertise in cloud-native architecture, containerized services, and microservice orchestration (Docker, Kubernetes)
Solid understanding of LLM-based pipelines, knowledge retrieval, and secure document processing
Strong experience with data systems like PostgreSQL, Elasticsearch, and Redis