Principal Product Manager, AI

About the Company Armada is the hyperscaler for the edge, delivering modular AI infrastructure from first deployment to AI factory with speed, scale and sovereignty. Named one of Fast Company's Most Innovative Companies and to the CNBC Disruptor 50, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense. With nearly $500 million in funding to date, Armada is backed by leading investors including Founders Fund, Lux, BlackRock and Microsoft (M12), alongside strategic partnerships with Microsoft, Dell, Palantir, NVIDIA, SpaceX, and Skydio. We are building the infrastructure layer for sovereign and edge AI - rugged, deployable compute for customers that cannot rely on centralized cloud. Working at Armada means taking ownership, driving autonomy, and delivering impact. You’ll tackle challenges that haven’t been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada’s mission to bridge the digital divide for customers around the world. About the role We are seeking a hands-on, execution-focused Principal AI Product Manager to lead the development and delivery of cutting-edge AI products that serve our Industrial and Public Sector customers. In this role, you will work closely with engineering, design, and go-to-market teams to bring [... source excerpt omitted ...] me, with measurable impact. This is a roll-up-your-sleeves position for a product leader who thrives on shipping high-quality products in complex, multi-stakeholder environments. You will focus on driving execution, owning the product lifecycle, and making AI innovation real for our customers. Location: This role is office-based at our Bellevue, Washington office. What You'll Do (Key Responsibilities) Drive Execution: Own the end-to-end delivery of AI products from requirements, Epics and user stories to development, QA, and launch in close collaboration with engineering and design teams. Product Delivery: Translate high-level product strategy into detailed, actionable produ [... source excerpt omitted ...] on real-world usage. Roadmap Input: Contribute to and maintain a tactical product roadmap that aligns with overarching goals. Prioritize features based on technical feasibility, customer value, and time-to-market. Cross-functional Collaboration: Work day-to-day with ML engineers, platform engineers, designers, and QA to ensure successful and timely delivery of product milestones. AI Use Case Implementation: Partner with engineering and data science teams to turn promising AI use cases (e.g., image classification, generative AI, predictive analytics) into reliable, production-ready features. Testing and QA: Coordinate user testing, manage edge cases, and proactively mitigate