Investment research platform building an AI research assistant on RAG
Seeking Alpha runs a crowd-sourced investment research platform on a dual data stack, with Hadoop, Spark and EMR alongside Kinesis, Airflow, Vertica and Redshift. The real signal is the LangChain, LangGraph and LangSmith footprint paired with projects around an "Ask Seeking Alpha" assistant, agent orchestration and hybrid search. Senior-weighted engineering and data hiring across Israel and Eastern Europe points to a serious generative AI build, not an experiment.
Seeking Alpha is a financial research platform founded in 2005 and headquartered in New York. It publishes stock analysis, investment ideas, earnings call coverage and quantitative ratings, much of it contributed by a large community of investors. The company is privately held and employs 201–500 people. Its product is built on AWS with a React and TypeScript front end, Python and Scala services, and a large-scale data platform behind site and app features. Hiring spans Ukraine, Israel, Poland and Portugal.
Seeking Alpha uses AWS (Lambda, EMR, Kinesis, Athena), Hadoop, Spark, Airflow, Vertica, Redshift, Elasticsearch, FastAPI, React, TypeScript, Tailwind CSS, Datadog and Sentry, plus LangChain, LangGraph and LangSmith for AI work.
Job posts point to an "Ask Seeking Alpha" AI system, including agent orchestration, agentic workflows, semantic caching, a RAG retrieval layer and hybrid search infrastructure.
Seeking Alpha is hiring in Ukraine, Israel, Poland and Portugal, mainly for senior engineering and data roles, and hiring is accelerating.
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Seeking Alpha's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.