The RoleAs Full Stack AI Product Manager, you'll be the catalyst for AI-driven operational transformation at Razorpay. Your mission is to eliminate inefficiency and elevate quality across internal teams by solving things via AI.This role is perfect for an AI enthusiast who thrives on experimentation. You'll march Razorpay forward in the direction of full-stack building via building or integrating video-coding stacks. And also do things that earlier wasn't just feasible.Working directly with the CPO, Design Head and product leadership team, you'll have the unique opportunity to shape how AI transforms the product management function. Key ResponsibilitiesAI Product Strategy & VisionIdentify high-impact use cases where full-stack building is relevant.Explore & scale prototyping as a culture across the org.Full Stack product buildingInternal AI Tools: Design and build productivity-multiplying tools that teams actually want to use, focusing on eliminating repetitive work and reducing time-to-completionAgentic Workflows: Create intelligent agents that can understand context, make decisions, and take actions across multiple platforms and data sourcesCross-Platform Integration: Build seamless connections between various internal tools, APIs, and data sources to create unified, intelligent workflowsHands-On buildingRapid Prototyping: Proficiently use no-code/low-code platforms like Replit, Lovable, and Cursor to build and test functional prototypes quicklyUnderstanding of UX & Design systems: Robust understanding of user experience and how design systems play a key role in the UX journeyEngineering: Understand basics of engineering to hands-on code if needed in the POC phase and productionise these early prototypes.Cross-Functional CollaborationPartner with Engineering, Data Science, Design, and Operations teams to bring full stack building to a reality and scale.Own a few of these e2e and then scale the GTM via the entire product & design team.Work with Compliance, Risk, and Legal teams to ensure AI implementations meet regulatory requirementsCollaborate with external vendors and ecosystem partners for AI infrastructure and specialized capabilities What We're Looking ForBachelor's degree in Engineering (Computer Science, Electronics, or related technical field) with 2 years of engineering experienceHands-on experience with design first productsHands-on experience building AI-powered solutions using no-code platforms (Replit, Lovable, Cursor)Strong analytical and problem-solving skills with comfort in rapid prototyping and iterative development