Senior Software Engineer / Search Engineer (Elasticsearch & Vector Search)

Role Overview: You will own the search infrastructure for Ask Seeking Alpha, a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, and news) in milliseconds. You will work on the Retrieval layer of our Retrieval-Augmented Generation (RAG) architecture, blending traditional keyword search with modern vector search techniques.

Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.

What You’ll Do: - Design and implement Hybrid Search strategies that combine keyword matching (e.g., tickers like AAPL) with semantic search (concepts like revenue growth). - Tune relevance to improve the quality of search results and build systems to measure improvements (e.g., with LangSmith). - Manage the integration of OpenAI embeddings into Elasticsearch; address indexing of long documents (earnings transcripts) so the AI retrieves only the most relevant parts. - Optimize Elasticsearch queries and index settings for low latency across complex filters. - Develop Python backend services that build queries and process results, leveraging FastAPI and Asyncio.

Senior Software Engineer / Search Engineer (Elasticsearch & Vector Search)

Role Overview: You will own the search infrastructure for Ask Seeking Alpha, a financial intelligence platform powered by LLMs. Your main goal is to ensure our AI agents can find the exact financial data they need (articles, transcripts, and news) in milliseconds. You will work on the Retrieval layer of our Retrieval-Augmented Generation (RAG) architecture, blending traditional keyword search with modern vector search techniques.

Tech Stack: Elasticsearch (v8+), Python (FastAPI, Asyncio), OpenAI Embeddings, LangChain, LangSmith.

What You’ll Do: - Design and implement Hybrid Search strategies that combine keyword matching (e.g., tickers like AAPL) with semantic search (concepts like revenue growth). - Tune relevance to improve the quality of search results and build systems to measure improvements (e.g., with LangSmith). - Manage the integration of OpenAI embeddings into Elasticsearch; address indexing of long documents (earnings transcripts) so the AI retrieves only the most relevant parts. - Optimize Elasticsearch queries and index settings for low latency across complex filters. - Develop Python backend services that build queries and process results, leveraging FastAPI and Asyncio.