Senior Program Manager

Microsoft•Redmond, WA

2d•$119,800 - $261,000

About The Position

The Compliance, Governance & Sustainability (CG&S) organization is seeking a Senior Program Manager in Redmond, Washington, to enable AI-native process and systems transformation. The role works across business, engineering, data, security, and compliance stakeholders to understand complex business needs, identify conditions for success, and translate them into scalable process, product, platform, and AI-enabled solutions. The successful candidate combines analytic problem solving, business process improvement, AI and technical proficiency, and program management to accelerate adoption, improve operational efficiency, and help CG&S shift toward predictive, automated, and intelligence-driven ways of working.

Requirements

Bachelor's degree in Computer Science, Engineering, Data Science, Math, Business, or a related field and 4+ years of experience in engineering, product/technical program management, data analysis, or product development, or equivalent experience.
Experience managing complex cross-functional projects or programs, including strategic planning, requirements definition, execution, risk and dependency management, stakeholder alignment, and delivery of measurable outcomes.
Demonstrated business process improvement and continuous improvement experience, including assessing current processes, identifying opportunities, evaluating alternatives, and implementing scalable solutions.
Analytic problem-solving and decision-making skills, including using facts, data, and logic to address ambiguous problems and make tradeoffs in a fast-paced environment.
Experience collaborating with technical and non-technical stakeholders and translating business needs into process, data, automation, product, or systems requirements.
Technical proficiency sufficient to evaluate and help implement integrated digital solutions, with working knowledge of AI-enabled productivity, agents, automation, data platforms, analytics, APIs, or related technologies.
Communication skills to convey strategic objectives, operational insights, requirements, tradeoffs, and value propositions to diverse stakeholders.
Commitment to responsible AI, privacy, security, confidentiality, accessibility, data governance, and compliance requirements when designing and deploying AI-enabled processes and systems.
Ability to learn emerging technologies and business domains quickly, identify appropriate applications, and support adoption through clear guidance, storytelling, and practical enablement.
Effective communication and stakeholder engagement skills.
Experience working in a matrixed, global organization.

Nice To Haves

Master's degree in Computer Science, Engineering, Data Science, Math, Business, or a related field and 6+ years of experience in engineering, product/technical program management, data analysis, or product development; or a bachelor's degree in a related field and 8+ years of experience in those areas; or equivalent experience.
Knowledge of AI-driven solutions and digital risk management platforms.

Responsibilities

Lead end-to-end AI-native transformation programs, from discovery and process analysis through requirements, solution design, implementation, adoption, measurement, and continuous improvement.
Partner with business stakeholders to identify needs, pain points, conditions of success, and opportunities to redesign processes using AI, agents, automation, data, and digital platforms; translate scenarios into requirements, functional specifications, roadmaps, milestones, and measurable outcomes.
Collaborate across engineering, architecture, data, security, and business teams to evaluate solution options, align technical approaches to business requirements, resolve blockers, and establish delivery and adoption cadences.
Capture stakeholder feedback, operational insights, telemetry, and lessons learned to identify patterns, improve solutions, inform future product and platform capabilities, and continuously improve business processes.
Drive adoption and change readiness by communicating strategic objectives and solution value, developing practical guidance and enablement, and helping stakeholders build fluency in AI-enabled and agentic ways of working.
Champion responsible, secure, and governed AI and data practices, including appropriate architecture and security reviews, role-based and least-privilege access, data quality, confidentiality, traceability, and auditability for sensitive or regulated scenarios.