Product Manager

Job description

**Overview** Commercial Engineering & AI (CEAI) is the frontier organization for Microsoft’s Commercial Business. We bring together AI‑native engineering, modern platforms, and deep commercial insight to reimagine how work gets done - at scale and with impact. Our mission is to unlock new ways of operating through intelligent systems while creating the conditions for our teams to do the most meaningful work of their careers. Customer Success Engineering (CSE) sits within CEAI and builds the AI-powered platforms, applications, and agents that transform how Microsoft engages, retains, and grows its customers. We operate as a builder organization — we ship, measure real usage, and ship again — pairing deep domain expertise with AI-assisted development to move from idea to validated value in days rather than quarters using Microsoft technology stack. If you’re excited to build, experiment, and shape the future of commercial execution with AI at the core, we invite you to apply. We are looking for a Product Manager who is equal parts Product Strategist and hands-on AI Builder. This is an AI-native product role: you won’t just define what to build — you’ll use AI to build it. You will set the strategy for the next wave of AI solutions across Microsoft’s Customer Success motion, then rapidly prototype and ship those solutions yourself using AI-assisted development. This role blends two operating modes. Great candidates are strong in both — and comfortable moving between them daily: **Product Strategist** - Owns the multi-quarter vision and roadmap for AI-first applications. - Frames the problem spaces, defines the bets, and sequences the portfolio. - Translates business goals into measurable product outcomes. - Aligns leaders, engineering, and design around a shared strategy **AI Builder** - Uses AI to build — prototypes and ships applications, agents, and workflows. - Turns concepts into working demos in days, not quarters. - Instruments builds with telemetry and evals for AI quality and impact. - Raises team throughput by applying AI to the product-development loop. Your work will directly impact multi-billion-dollar businesses — fueling revenue growth, sharpening competitive advantage, and optimizing margins. You will also push the latest AI frontiers, including autonomous agentic workflows, deep research and reasoning, and multi-agent frameworks, while maintaining a relentless focus on high-quality user experiences — from conversational UX to emerging interaction models across the Microsoft and Copilot ecosystem. Just as importantly, you will use AI to raise the productivity of the entire product organization, establishing the tools, patterns, and evals that let the team ship better products, faster. **Requirements** This role reflects how product management is evolving in CSE — from requirements author to builder and decision architect. We look for people who consistently demonstrate four shifts: - Builder, not just author. Move beyond specifications to build lightweight business models, decision flows, prototypes, and AI-assisted experiments that stakeholders can evaluate before engineering commits — using AI-assisted development to check in production-ready code for enhancements where it accelerates learning. The goal is to shrink the distance between an idea and validated business value. - Systems thinker. Sees every feature as a node in a larger system rather than a standalone deliverable — thinking end-to-end from upstream inputs to downstream impact. Asks "how should the system behave to achieve the outcome?" rather than "what feature should we build?" Uses AI to model systems, expose hidden dependencies, generate edge cases, and evaluate downstream impacts before implementation begins. - Intelligent orchestrator. Treat AI as a reasoning partner that challenges assumptions, proposes alternatives, and automates routine coordination — synthesizing requirements, summarizing decisions, and surfacing risks — so your time is reinvested in ambiguous problems and strategic calls. - Decision architect. Shifts from "is the requirement complete?" to "do we have evidence the solution will achieve the outcome?" Defines evals up front and lets data — not opinion — drive the call, generating evidence through business-rule simulation, scenario modeling, edge-case generation, and prototype validation. Correctness before code. **Responsibilities** **Responsibilities** **Set the Strategy** - Own the vision and roadmap. Define a multi-quarter product strategy for AI-first applications, translating business goals into a coherent portfolio of prioritized scenarios and bets. - Envision the next wave. Lead scenario envisioning and UX & technical product design for agentic and Copilot-powered experiences; advise on GTM, adoption, and evolving portfolio strategy. - Shape long-term direction. Capture, frame, and drive key product insights and ecosystem signals from the market to shape the future of Microsoft AI platform, apps, and toolset. - Lead prioritization, backlog management, and cross-team alignment, focusing teams on the highest-impact work **Build with AI** - Prototype, don’t just spec. Use AI to rapidly build applications, agents, and workflows with Copilot Studio, Power Platform, Azure AI Foundry, Azure OpenAI, and AI-assisted (low-code / “vibe coding”) development. - Turn concepts into working software. Stand up functional demos and pilots in days, validate them with real users, and iterate quickly toward production. - Ship production quality. Partner with engineering to build and ship robust, reliable, inclusive experiences — owning quality and adoption end to end. - Instrument everything. Define telemetry, dashboards, and evaluations to measure AI quality (accuracy, groundedness, latency) and business impact; use the data to validate improvements and inform decisions. - Put AI in your build pipeline. Use AI-assisted coding (e.g., GitHub Copilot), AI-generate