Findem runs an AI talent-decision platform on a big-data stack: Kafka, Spark, Hadoop, Airflow, Presto, Athena and Redshift feeding Snowflake, with Python and Scala in the mix. MCP in the stack suggests the product is exposing its people data to AI agents. Hiring is accelerating and weighted toward senior and principal product roles, alongside ISO 27001 compliance and IT automation work that point to enterprise readiness.
Findem builds an AI platform that helps organizations make talent decisions across hiring, executive search, internal mobility, learning and workforce planning. Its engine labels large volumes of unstructured people data into signals about what drives success and how people are connected. The company was founded in 2019, is privately held and is headquartered in Redwood City, California. It employs 51–200 people and hires in the United States and India. Go-to-market runs on HubSpot with paid campaigns across Google, Meta and LinkedIn.
Findem's data stack includes Kafka, Apache Spark, Hadoop, Airflow, Presto, Athena, Redshift and Snowflake on AWS. It builds with Python, Scala, Node.js and MongoDB, and uses HubSpot, Jira and Slack.
Findem is headquartered in Redwood City, California. It hires in the United States and India.
Yes. Findem's hiring is accelerating and centers on product roles at senior and principal levels, with additional openings in support and marketing in the US and India.
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Findem'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.
