Senior Product Manager - Search

Datadog•New York, NY

2d•$192,000 - $240,000•Hybrid

About The Position

Datadog’s Search team helps users – both human and agents – find answers to their questions. Search is a critical function in Datadog, and touches many product surfaces: the query editors in product homepages and dashboards, search bars for finding relevant assets, the global cmd+k navigation search, and the MCP tools that our Bits AI agent uses to respond to natural language prompts. Search is a full-stack team: owning user-facing search components, backend search ranking systems, and machine learning models to produce recommendations. The Search team is relatively new, and still growing. We have recently built out agentic search tools, and we are looking for a leader to help us expand to ambitious orchestration systems that deliver accurate results, and proactive recommendations across both keyword and semantic search. Beyond this, you’ll have room to influence how Datadog thinks about Search as a strategic surface.

Requirements

You have experience with search, ranking, or recommendation systems
You are familiar with or very interested in MCP servers and differences between human and agentic UX
You have a sharp eye for design and strong opinions on the micro-interactions — keyboard navigation, autocomplete behavior, loading states — that separate a good search experience from a great one
You have a strong technical background, and sense of the day in the life of an engineer operating large-scale data systems
You have excellent verbal and written communication skills and the willingness to present and defend your ideas to technical stakeholders and executives alike
You have 5+ years product experience

Responsibilities

Define and deliver how Datadog's AI agents discover the right context and tools to answer natural-language questions accurately and at scale
Stay on top of industry trends in UI and agentic search experiences and capabilities
Collaborate with Applied AI teams to integrate ranking, personalization, and recommendation models that scale across both human and agentic users
Define and monitor KPIs for search quality, adoption, and downstream impact on user productivity; use them to drive data-informed decision making
Engage directly with customers and internal product teams to deeply understand search journeys across query editors, global navigation, and natural-language agent interfaces