Principal Product Manager
Microsoft (Eightfold Apply)
- Location
- United States, Washington, Redmond; United States, Multiple Locations, Multiple Locations
- Work model
- On-Site
- Level
- Principal
- Posted
- 2h ago
About this role
Overview
Commercial Engineering & AI (CEAI) is modernizing how Microsoft builds and operates customer, partner, and employee experiences for its commercial business. CEAI brings together agents, engineering tools, data, insights, and direct customer feedback to shorten the path from business need to measurable impact and help Microsoft’s commercial business operate as a frontier organization. The AI Engineering Excellence team defines and scales how CEAI applies AI across the software lifecycle. We establish engineering practices, workflows, and reusable capabilities that teams can adopt broadly while incubating breakthrough approaches that are not yet ready to standardize. AI-native engineering spans the full journey—from understanding customer needs and shaping solutions to building, validating, deploying, operating, and continuously improving them—not merely generating code with AI. Our primary focus is defining, analyzing and improving the agent-driven workflows that drive the software development lifecycle. We prove these capabilities in real engineering environments, measure their impact, turn successful patterns into repeatable practices and scale them across the organization. We will also identify where the organization can benefit from common foundations and platform capabilities, incubate services and tools and scale and operate them. We see a generational opportunity to expand human creativity and productivity through rapid experimentation, disciplined measurement, and continuous learning. As a Principal Product Manager, you will be a founding product leader for this mission. You will identify the engineering problems where agents can create the greatest value, translate ambiguous signals into a focused strategy and roadmap, and lead capabilities from initial experiment through production adoption and measurable impact. You will work directly with users and partner with engineering, design, research, and product teams to evaluate emerging models and tools, make investment tradeoffs, and improve developer productivity, ship velocity, and the overall engineering experience.
Responsibilities
Define and drive the product vision, investment strategy, roadmap, and success measures for the AI-native engineering workflows and agent capabilities CEAI will build, validate, and scale. Identify high-value opportunities for agents to improve the full software lifecycle, from understanding customer needs and shaping solutions through implementation, testing, review, deployment, operations, and learning. Maintain close feedback loops with engineering and product teams, turning developer pain points, behavioral signals, and emerging needs into clear product requirements and scalable solutions. Instrument, measure, and improve developer productivity, efficiency, ship velocity, adoption, and the overall developer experience, using both quantitative and qualitative evidence. Incubate, test, and evaluate emerging AI development tools, models, and platforms; assess their applicability in complex production environments and translate promising approaches into durable capabilities. Lead 0→1 experimentation and incubation, moving quickly from hypothesis to working capability, production validation, adoption, and measurable impact. Shape enabling platform investments, including golden paths, repository and migration tooling, shared foundations, test environments, identity, secrets, configuration, observability, and safe deployment. Partner with engineering leaders on architecture, dependencies, operational readiness, prioritization, investment tradeoffs, and risk management. Participate in senior engineering forums and cross-organizational v-teams, influencing technical and product direction without relying on direct authority. Model AI-native product development in practice, mentor product managers and cross-functional partners, and raise the bar for clarity, experimentation, execution, and platform-as-product thinking.