Overview
We are hiring for a Principal Product Manager to help build the next generation of content platform for Microsoft AI’s Content team. This role will focus on AI-native personalization systems that understand users over time, recommend the right high-quality content and experiences, and generate personalized content that inspires, informs, and engages millions of users across Microsoft surfaces.
Personalization is evolving from traditional ranking and recommendation into a broader intelligence layer: generative recommendation systems, agentic user understanding and memory, personalized content generation, and closed learning loops that help products adapt to each user’s intent, context, feedback, and long-term interests. This is an opportunity to define a new personalization category at the intersection of AI, recommendations, user memory, content intelligence, and generative experiences, shaping how millions of users discover content that feels timely, useful, trustworthy, and personally relevant.
In this role, you will define product direction for this platform, translate AI and model capabilities into user-facing value, and partner closely with engineering, research, data science, design, legal, privacy, and business teams to move capabilities from research prototypes into scalable personalization systems and user-facing experiences. You will work across recommendation systems, user and content understanding, agentic memory, generative AI content, evaluation, experimentation, and platform infrastructure.
This role is ideal for a PM with strong product taste and judgment, technical depth, data fluency, and experience building consumer AI, recommendation, personalization, or platform products in ambiguous, high-impact environments. The right candidate will combine consumer product intuition with systems rigor, caring about both the quality users feel and the infrastructure that makes personalization repeatable at scale.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
- Define the product vision, strategy, and roadmap for AI-powered personalization across recommendation systems, user and content understanding, agentic memory, and generative AI content experiences.
- Translate user and product goals into clear requirements for ranking, retrieval, profile generation, memory, content understanding, data pipelines, evaluation, and serving systems.
- Turn advances in AI, ML, LLMs, ranking, retrieval, and generative recommendation systems into practical product capabilities that improve user engagement, satisfaction, trust, safety, and business impact.
- Own product requirements and platform interfaces for recommendation systems, user profiles, memory, personalization signals, AI content generation, human and AI evaluation, and downstream product integration and consumption.
- Partner with engineering, research, data science, design, legal, privacy, and policy teams to move capabilities from research prototypes into scalable personalization systems and user-facing experiences.
- Define success across offline evaluation and online product metrics, balancing relevance, usefulness, freshness, latency, safety, reliability, cost, and long-term user value.
- Build closed learning loops that turn product usage, explicit feedback, content signals, and model outcomes into datasets, evaluations, experiments, training priorities, and launch decisions.
- Use experimentation, telemetry, user research, and model evaluation to identify opportunities, prioritize investments, and validate product impact.
- Work with infrastructure and platform teams to balance model capability, latency, serving cost, data freshness, privacy constraints, and system reliability.
- Create clear product artifacts, decision frameworks, and roadmap documents that align teams across ambiguous and cross-functional workstreams.
- Influence senior stakeholders and partner teams by explaining complex AI, ranking, and platform tradeoffs in clear business and user terms.
Qualifications
Required Qualifications:
Bachelor's Degree AND 10+ years experience in product/service/program management or software development
- OR equivalent experience.
Preferred Qualifications:
Bachelor's Degree AND 15+ years experience in product/service/program management or software development
- OR equivalent experience.
Experience building or managing AI, ML, recommendation, personalization, search, content understanding, user understanding, or data platform products.
Experience using data, experimentation, user feedback, and product metrics to guide roadmap decisions and measure product impact.
Experience working with cross-functional teams, including engineering, data science, research, design, privacy, policy, or go-to-market teams.
5+ years’ experience building consumer-facing AI, recommendation, personalization, search, feed, marketplace, content, or platform products.
Experience with generative AI, LLMs, agents, user memory, retrieval systems, ranking systems, or AI-powered content generation.
Experience defining product architecture for personalization platforms, including user profiles, signal pipelines, model interfaces, evaluation systems, serving systems, and downstream product integrations.
Experience launching 0-to-1 products or platform capabilities in ambiguous, fast-moving environments.
Experience improving product metrics such as engagement, retention, relevance, satisfaction, revenue, content quality, or recommendation performance.
Solid technical fluency with AI/ML systems, data pipelines, APIs, experimentation, telemetry, model evaluation, and scalable serving infrastructure.
Working knowledge of SQL, Python, experimentation platforms, analytics tools, or data investigation workflows.
Ability to combine consumer product taste with systems rigor, caring about both the quality users feel and the infrastructure that makes personalization repeatable at scale.
Ability to write clear product documents, align multiple teams, and drive decisions across technical and business stakeholders.
Solid product judgment, systems thinking, user empathy, and ability to operate with high agency in complex product areas.
#MicrosoftAI
Product Management IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about **requesting accommodations.**