Principal Product Manager AI Data Platform

Principal Product Manager For Microsofts Ai Data Platform

The Principal Product Manager for Microsofts AI Data Platform is a strategic leader responsible for driving the vision, execution, and impact of a central platform that manages the full lifecycle of first-party, third-party, synthetic, and human-labeled data for AI training across Microsoft. This role is mission-critical to breaking down data silos, maximizing ROI on data investments, and accelerating AI model development.

At Microsoft, our mission is to empower every developer and organization to achieve more with AI. As part of the CoreAI organization, the Data for AI team sits at the heart of this mission : we design and operate Microsofts central AI data platformthe backbone for acquiring, curating, synthesizing, and governing the data that powers our most advanced language and multimodal models.

As a Principal Product Manager for Data for AI, you will define and drive the vision for the data lifecycle spanning first-party, third-party, synthetic, and human-labeled data. You will lead a team of PMs and partner deeply with engineering, research, legal, compliance, and business stakeholders to make high-value datasets discoverable, reusable, cost-efficient, and compliant. This role is critical to maximizing ROI on Microsofts data investments, accelerating model innovation, and ensuring responsible AI at scale.

We are looking for a proven AI / ML product leader with startup scrappiness and Big Tech scale experience - someone who thrives in ambiguity, has a track record of execution, and can unify a complex ecosystem into a coherent platform strategy.

Success in Role :

• Launching a unified cross-company data platform that reduces redundancy and accelerates access to high-value datasets.
• Accelerating acquisition, curation and impact of high quality datasets across multi-modal scenarios
• Establishing data provenance guarantees that become a benchmark for responsible AI at Microsoft.
• Delivering measurable improvements in data quality, model performance, and cost efficiency.
• Building a high-performing PM team recognized for clarity, velocity, and impact.