AI-driven hiring and workforce platform for frontline employers
Fountain builds AI-driven software that automates high-volume hiring, retention and operations for frontline workforces. Its stack pairs Ruby on Rails and Node.js with a heavy data layer (dbt, Dagster, ClickHouse, Snowflake, BigQuery, Redshift) on Kubernetes and EKS with ArgoCD and KEDA, a platform-engineering setup built for bursty traffic. Accelerating, senior-heavy hiring splits between engineering and sales, with job posts focused on making agentic systems and agent-written code reliable.
Fountain is a privately held software company founded in 2014 and headquartered in San Francisco, California, with 201–500 employees. It sells a modular platform to HR and operations teams at employers with large frontline workforces in sectors such as logistics, retail and healthcare. The product covers mobile-first, high-volume recruiting with automated workflows and analytics, alongside retention and workforce operations tools driven by AI agents. The company operates remotely and hires across the United States, Brazil, Sweden and Portugal.
Fountain uses Ruby on Rails, Node.js, Express.js, React and TypeScript, with MongoDB and PostgreSQL, a data stack of dbt, Dagster, ClickHouse and Snowflake, and Kubernetes on AWS EKS managed via Terraform, Helm and ArgoCD.
Yes. Hiring is accelerating and mostly senior, split mainly between engineering and sales, with data roles also open. Searches cover the United States, Brazil, Sweden and Portugal.
Job posts point to agentic development workflows for the data team, autoscaling and observability upgrades, infrastructure-as-code improvements, and design work on interfaces shared by humans and AI agents.
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Fountain'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.