Agentic product management system with a built-in AI product agent
Productboard builds an AI-agent-driven product management platform for product teams, running on a polyglot stack of Ruby on Rails, Kotlin, Java, Python and TypeScript over Kafka, PostgreSQL and Kubernetes on AWS. LangGraph alongside Cursor and Codex shows AI reaching both the product and the engineering workflow. Staff-level, engineering-heavy hiring targets agent evaluation, self-healing incidents and AI code review, signaling a push to re-architect around AI-native development.
Productboard, founded in 2014 and headquartered in San Francisco, makes product management software centered on Spark, a built-in agent that works with a company's product data and documents conversationally. The platform supports core product workflows such as identifying customer needs, turning ideas into specs ready for delivery, and measuring the impact of shipped work. It sells to product teams at businesses of varying size. The privately held company employs 201–500 people, with offices in Prague and San Francisco, and runs a sales motion supported by Salesforce, Gong and Outreach.
Productboard uses Ruby on Rails, Kotlin, Java, Python, React and TypeScript, with Kafka, PostgreSQL, Redis and Elasticsearch, deployed on AWS with Kubernetes and Terraform. LangGraph, Cursor and Codex support its AI work.
Yes. Hiring is accelerating and centers on staff-level engineering roles in the United States, with an additional lead-level marketing role, focused on AI agent workflows and AI-native architecture.
Current initiatives include an AI-native codebase architecture, agent workflows beyond chat, evaluation systems for AI agents, structured documentation for agents, GTM infrastructure, and AI-driven onboarding experiments.
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Productboard'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.