Manager I, Engineering - Applied AI/ML Product Analytics Suite

At Datadog, a Most Loved Workplace® certified employer in the Technology space, Observe, Secure, and Optimize Modern Cloud Infrastructure at Scale.

<p>Datadog’s Product Analytics suite spans Product Analytics, Session Replay, Feature Flags, and Experimentation. Together they give product teams a complete, quantitative and qualitative picture of how users experience their applications, plus the tools to release, measure, and improve those experiences with confidence.</p>

<p>Our team of Applied Scientists makes this space smarter and more autonomous, researching, prototyping, and industrializing AI/ML capabilities that make the suite proactive and agentic by default: AI-driven event understanding and instrumentation, conversational analytics, automated insight reporting, and UI/UX issue detection from session replays. The ambition is to let product teams act with autonomy, moving from question to insight to safely released change without depending on engineering or analysts.</p>

<p>As the Engineering Manager for this team, you’ll lead a team of Applied Scientists through an early-stage, high-impact opportunity: defining the team’s technical vision, growing its footprint, and shaping how AI capabilities get built and delivered across the suite. This is greenfield work, both in the R&D itself and in the team you’ll grow around it.</p>

<p><em>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.</em></p>

<p><strong>What You’ll Do:</strong></p>

<ul>

<li>Lead and grow a team of Applied Scientists researching, prototyping, and industrializing AI/ML capabilities across the suite</li>

<li>Define the technical vision and roadmap for the suite’s agentic and proactive AI/ML capabilities: event understanding, conversational analytics, insight reporting, and session-replay issue detection</li>

<li>Stay hands-o

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