Microsoft Principal Program Manager Responsible AI Practice 

United States, Washington 

523657163

Required Qualifications

• Bachelor’s Degree in Business, Operations, Finance or related field AND 8+ years work experience in program management, process management, process improvement
  • OR equivalent experience

Preferred Qualifications

• Experience approaching Responsible AI as a sociotechnical challenge rather than a purely technical one.
• Experience working in or with a large, matrixed organization.
• Highly developed written and oral communication skills.
• Proven track record of being able to engage and influence a variety of stakeholders. A key attribute will be the ability to work across multiple disciplines and cultures.
• Consistent record of being an effective team player dedicated to collective successes. The ability to promote cooperation and solve problems in a timely, creative, and professional manner. Proficiency at working closely and collaboratively with multiple departments and executives, and in cross-functional teams.
• Ability to navigate ambiguity and adapt to rapidly changing environments and demands.
• Consistent record of experimentation, learning from both successes and failures.
• Demonstrated commitment to the company’s core values, including a commitment to high ethical standards, unquestioned integrity, and a commitment to advancing the company’s diversity & inclusion commitments.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until June 20, 2024.

• Drive orchestration and integration efforts for large, mission critical, complex cross functional projects with Responsible AI teams across policy, engineering, and research to achieve policy priority goals.
• Facilitate effective and accurate communication amongst stakeholders, translate disparate organizational goals into aligned priorities, and drive accountability.
• Produce policy artifacts, implementation guidance, and other materials aimed at supporting effective and efficient effort by engineering teams towards compliance.
• Identify potential risk areas, dependencies, and technical blockers, and drive mitigations and solutions.
• Partner with engineers, researchers, and others to create policy creation and implementation processes, using maturity frameworks to track, collect performance metrics, monitor and report on progress and derive deep insights thatimprove Responsible AI practice and governance.
• Embody our and