Process orchestration platform embedding governed AI agents into enterprise workflows
Bizagi builds a low-code process automation platform on a .NET, C#, Angular and SQL Server core, hosted on Azure with AWS, Docker and Kubernetes also in the stack. Job posts point to an active migration of the product to the cloud alongside integration of AI agents, workers and assistants. Hiring is accelerating and engineering-led, with a finance and legal build-out tied to LATAM growth and North American contracting.
Bizagi is a privately held software company founded in 1989 and headquartered in Washington DC, with 201–500 employees. It sells an enterprise orchestration and business process management platform that combines workflow automation, process modeling and low-code development. The platform embeds generative AI capabilities, including AI agents, AI workers and a natural-language assistant, into end-to-end business processes with role-based governance. It runs on Microsoft Azure and serves enterprises across sectors such as financial services and manufacturing. The company hires in the United States and Colombia.
Bizagi's stack centers on .NET, C#, Angular, NgRx, RxJS and SQL Server, running on Azure and AWS with Docker, Kubernetes and Grafana. Java, Python, Node.js, Workday, SAP and Zendesk also appear.
Job posts show Bizagi integrating AI agents, workers and assistants into its platform, migrating its product to the cloud, and building commercial contracts and privacy policies for North America and EMEA.
Bizagi is hiring in Colombia and the United States, with demand concentrated in engineering plus finance, legal, security, marketing and operations roles.
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Bizagi'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.