Overview
Be at the forefront of AI by joining the M365 AI Platform team.
Role Summary:
As a Senior Product Manager on the M365 AI Platform team, you will help define product requirements, shape roadmaps, and drive execution for AI-driven initiatives.
What You’ll Gain:
- A unique opportunity to work on high-impact, forward-looking projects at the intersection of research and product.
- Mentorship and growth within a world-class product team.
- A collaborative environment that values intellectual curiosity, experimentation, and humility.
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.
Qualifications
Required Qualifications:
- Bachelor's Degree AND 5+ years experience in product/service/project/program management or software development
- OR equivalent experience.
- Experience in product management or a technical role with customer-facing responsibilities.
- Demonstrated ability to work with technical teams on complex, data-driven or ML-based products.
- Solid analytical skills and comfort with ambiguity in problem spaces.
- Experience with AI/ML or data products is a strong plus; interest in scientific domains is essential.
- Excellent written and verbal communication skills, with the ability to engage both technical and non-technical audiences.
Preferred Qualifications:
- Technical background (BS in Computer Science, Engineering, or related field); advanced degree is a plus.
- Familiarity with the AI/ML development lifecycle, model evaluation, and experimentation frameworks.
- Experience in early-stage product development or 0-to-1 environments.
Responsibilities
- Collaborate across disciplines to shape the future of the Core of AI in M365.
- Gather customer and business requirements and translate them into clear, actionable product specs.
- Support prioritization of features and investments based on impact, feasibility, and alignment with research progress.
- Define and track success metrics, leveraging experimentation and data insights to validate assumptions.
- Drive cross-functional execution in a structured and iterative way, balancing agility with product discipline.
- Clearly communicate plans, decisions, and trade-offs to stakeholders.
