Tech Stack
CloudDockerElasticSearchKubernetesPostgresRedis
About the role
- Architect, scale, and own the core systems that power Ema’s Search platform.
- Own the technical roadmap for Search, including core platform, internal and partner integrations, and Open API specs.
- Set the roadmap for the Data Ingestion Platform to securely ingest, transform, and index documents, spreadsheets, emails, and SaaS data.
- Lead the Application Integration Platform connecting Ema to third-party APIs (CRMs, ITSMs, HRIS, etc.).
- Design and scale Search Platform to enable structured and unstructured data for search, reasoning, and generation.
- Own architecture and implementation of Ema’s Search Index.
- Drive and collaborate with LLMOps infrastructure and enable external transform development.
- Ensure platform support for diverse data formats (PDFs, spreadsheets, databases, charts) using PostgreSQL, Elasticsearch, and other 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.