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Datadog is seeking a Director of Product Management to lead the AI Observability portfolio and define how organizations build, monitor, and scale AI systems in production. This role owns the vision and strategy for LLM Observability, GPU Monitoring, Distributed AI Monitoring, and emerging research-oriented tooling such as Model Lab.
You will set the strategic direction for this rapidly growing area, expanding established products while incubating new capabilities that deliver deep visibility into AI infrastructure, model performance, and distributed AI environments. As AI becomes core to modern applications, this team plays a critical role in ensuring customers can deploy and scale AI with confidence.
Key responsibilities include owning the product vision and strategy aligned with company goals and customer needs; leading and mentoring a team of product managers; collaborating with engineering, data science, marketing, and sales to deliver AI solutions; identifying new opportunities for AI product innovation; working closely with customers to understand pain points; defining AI product roadmaps and managing feature prioritization; driving data-driven decision-making; promoting a product-first mindset; and fostering a culture of innovation in AI product development.
You bring proven experience in AI product management with a track record of successfully leading AI-driven product development and delivery. You have deep technical knowledge of AI technologies, machine learning, and data science, with the ability to translate these into compelling product experiences. You have successfully led product teams, mentored product managers, and balanced leadership with hands-on execution. You excel at prioritizing complex product roadmaps, collaborating across functions, and maintaining a customer-first mindset. You are a strong communicator and influencer capable of building relationships with senior leadership and external stakeholders. You have demonstrated ability to manage large-scale AI product initiatives and use AI coding tools in day-to-day workflows. Bonus: motivation to push boundaries of how AI can improve software engineering practices.
