Senior Software Engineer \ Search Engineer (Elasticsearch)

Що робити

Search Engine Development: Design and implement Hybrid Search strategies. You will figure out how to best combine "keyword matching" (finding specific tickers like 'AAPL') with "semantic search" (finding concepts like 'revenue growth').
Relevance Tuning: You are responsible for the quality of search results. You will build systems to measure and improve how well the search engine answers user queries (using tools like LangSmith).
Vector Search & RAG: Manage the integration of OpenAI embeddings into Elasticsearch. You will solve challenges related to indexing long documents (e.g., earnings transcripts) so the AI retrieves only the most relevant parts.
Performance Optimization: Optimize Elasticsearch queries and index settings to ensure low latency, even for complex queries with many filters.
Python Backend: Develop and maintain the Python services that build queries and process results. We use FastAPI and Asyncio heavily.

Elasticsearch Expert: 5+ years of experience working with Search Engines in production. You understand how indices, analyzers, and mappings work "under the hood."
Search Theory: You understand the difference between Lexical Search (keywords) and Vector Search (meaning), and know when to use which.
Python Proficiency: Strong experience with Python 3.10+. You are comfortable writing asynchronous code (async/await) and building APIs.
Data Engineering: Experience designing data schemas for search (how to structure JSON documents for efficient retrieval).

Experience building RAG (Retrieval-Augmented Generation) pipelines.
Familiarity with LangChain or similar LLM frameworks.
Experience with Evaluation tools (like LangSmith) to test search quality automatically.
Background in Finance (understanding tickers, earnings calls, etc.).

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