The posting, in Datadog's own words
archived Oct 9, 2026As organizations move AI agents from experimentation into production, engineering teams need to understand whether those agents are accurate, reliable, performant, and cost-effective. Datadog Agent Observability helps teams understand, evaluate, and improve AI agents across the development lifecycle. By connecting agent traces and evaluations with full-stack production telemetry, Datadog gives teams the context they need to understand agent behavior and resolve problems quickly. As the Product Manager for Agent Observability, you will own capabilities that help customers develop and operate reliable AI agents. You will spend significant time with customers, learn how they work, identify their most important problems, and translate those insights into a clear product strategy and roadmap. To succeed in this role, you should be comfortable navigating a rapidly evolving market, presenting to customers, and leading cross-functional efforts to drive adoption and growth. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.
What You’ll Do
Own the roadmap for new Agent Observability capabilities Develop a deep understanding of how teams build, evaluate, monitor, and troubleshoot AI agents Engage directly with customers and design partners to validate problems, test product concepts, and improve the product Work closely with engineering and design to deliver new capabilities from early concepts through launch and iteration Partner with GTM teams on positioning, sales enablement, customer education, and adoption Track developments across the broader AI ecosystem to guide priorities
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Who You Are
3+ years of PM experience, ideally in the AI/ML space Working knowledge of how AI agents are built and operated, or have hands-on experience with AI Observability or tooling Take ownership of outcomes and have a strong bias for action 0 to 1 experience is preferred