The AI Product Manager owns the strategy and execution of HSI’s customer-facing AI solutions, including the underlying Model Context Platform (MCP) and supporting AI services. This role delivers intelligent, context-aware product experiences powered by LLMs, automation, and data. You bring strong product fundamentals, a practical understanding of AI systems, and an AI-native approach to building products—leveraging AI to accelerate ideation, delivery, and iteration. Key Responsibilities Define and own the roadmap for a virtual assistant–driven application interface, including conversational experiences, agent capabilities, and workflow automation Lead the evolution of HSI’s MCP, including context management, memory, orchestration, and service integrations Translate company strategy and customer needs into differentiated AI-driven product capabilities Partner with engineering and data teams to design AI-powered features leveraging LLMs, RAG, and agent-based systems Define product requirements, including system behavior, prompts, guardrails, and evaluation criteria Drive execution through agile development cycles, maintaining a well-prioritized backlog of features and experiments Establish and monitor AI performance metrics (e.g., accuracy, task success, latency, cost, hallucination rates) Lead experimentation to improve model outputs, workflows, and user experience Partner with data teams to define feedback loops, data requirements, and opportunities for fine-tuning or optimization Use AI tools to accelerate core PM workflows, including requirements documentation, backlog refinement, and internal communications Rapidly prototype conversational flows and AI interactions to validate ideas early Synthesize customer feedback, support data, and usage patterns into actionable insights Continuously evaluate and adopt new AI tools to improve product development speed and decision-making Conduct user research and analyze customer workflows to identify high-impact AI opportunities Partner closely with engineering, UX, data science, and go-to-market teams to deliver cohesive solutions Serve as an internal advocate and subject matter expert for AI-driven product capabilities What Success Looks Like Measurable customer value and adoption High-quality, reliable AI features that continuously improve MCP evolves into a scalable, differentiated platform capability Increased product development velocity and insight generation through effective use of AI
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