Senior Product Designer, Monetization

Microsoft•Redmond, WA

15h•Onsite

About The Position

The Senior Product Designer will join Microsoft’s Monetization Inventory Design team to shape current and future monetization experiences across Microsoft Copilot, Bing (including AI Overviews and AI Mode), MSN, gaming, and other consumer surfaces. The role spans existing advertising experiences and exploration of new AI-enabled models that create value for consumers and businesses. This is a design, building, and systems-thinking role focused on reimagining how product design works in the AI era. The designer will create intelligent systems and AI-powered workflows that generate, critique, evaluate, refine, and operationalize design work. This includes building and orchestrating specialized AI agents, custom tools, prototypes, automations, and recursive systems that learn from research, experimentation, product signals, and human feedback. The role emphasizes applying human judgment to customer understanding, strategy, design direction, partnerships, and quality while encoding design principles, customer knowledge, interaction patterns, brand standards, and evaluation criteria into reusable systems. The designer will define and assess quality for AI-driven experiences and work closely with Product, Engineering, Data Science, Research, Design, and business teams to turn customer needs and technical capabilities into useful, differentiated experiences. For the Mountain View, California location, candidates must be local to the San Francisco Bay Area and work in-office four days per week. Redmond, Washington candidates must be local to the greater Seattle metropolitan area and work in-office four days per week. Microsoft AI employees within the specified commuting distances are expected to work from a designated office at least four days per week beginning January 26, 2026, subject to local law and jurisdiction.

Requirements

A Master's degree in Industrial Design, Product Design, Human Computer Interaction, User Experience, Interaction Design, or a related field and 4+ years of product or service design experience; or a Bachelor's degree in one of these fields and 5+ years of product or service design experience; or equivalent experience.
Exceptional product, interaction, and visual design judgment, with a portfolio or body of work demonstrating high-quality digital products shipped.
Hands-on experience building and orchestrating AI-powered workflows or agentic systems, including agents that use tools, context, delegation, evaluation, and feedback to accomplish complex work.
Evidence of personally building functional AI-driven systems, tools, or experiences that materially changed how a problem was explored, designed, or solved; conceptual familiarity with AI alone is insufficient.
Solid understanding of LLMs and generative AI, including prompting, context engineering, model and tool orchestration, structured outputs, retrieval, and evaluation.
Working knowledge of HTML, CSS, JavaScript/TypeScript, Python, or similar technologies, with the ability to independently create and modify functional prototypes and tools.
Experience working with APIs, structured data, models, tools, and external services to construct end-to-end AI experiences.
Solid understanding of evaluation for probabilistic systems, including defining quality criteria, identifying failure modes, and designing feedback and recovery mechanisms.
Ability to encode design taste and quality into principles, constraints, prompts, evaluations, tools, and systems.
Ability to establish direction in ambiguous technical spaces and transform emerging technology into understandable, useful, and differentiated customer experiences.
Solid product judgment and ability to connect customer needs, technology, research, business context, and measurable outcomes.
Ability to explain complex AI systems clearly and build alignment across Product, Engineering, Research, Data Science, Design, and business leadership.

Nice To Haves

A Master's degree in Industrial Design, Product Design, Human Computer Interaction, User Experience, Interaction Design, or a related field and 6+ years of product or service design experience; or a Bachelor's degree in one of these fields and 8+ years of product or service design experience; or equivalent experience.
Experience building multi-agent, recursive, or self-improving systems that evaluate outputs, incorporate feedback, and iteratively improve subsequent work.
Experience creating AI-powered design tooling, automation, or systems that expand the capabilities of other designers.

Responsibilities

Own and ship high-quality AI-powered consumer experiences from early exploration through implementation, maintaining high standards for interaction quality, visual craft, accessibility, trust, and customer impact.
Create AI-powered workflows that generate, critique, evaluate, refine, and operationalize design work at scale.
Build and orchestrate AI agents with specialized roles, tools, context, memory, and responsibilities, including how they delegate work, share context, evaluate outputs, incorporate feedback, and escalate decisions to people.
Develop recursive and learning design systems that use research, experimentation, product signals, evaluation, and human feedback to improve their outputs.
Build custom tools, prototypes, automations, and agentic workflows using code, models, APIs, structured data, and emerging AI technologies.
Encode design principles, customer knowledge, interaction patterns, brand standards, and quality criteria into reusable systems.
Design intelligent product behaviors that give people appropriate understanding and control, including intent, delegation, system status, uncertainty, correction, recovery, and human oversight.
Define quality standards for AI-driven experiences and build evaluation mechanisms to assess quality, identify failure modes, and improve systems.
Partner with Product, Engineering, Data Science, Research, Design, and business teams to connect customer needs with technical capabilities and influence system requirements.
Identify repeated human effort that can be scaled through automation, delegation, orchestration, or continuous learning.
Share tools, agents, patterns, and learnings so individual experimentation can become reusable organizational capability.