Product Manager

About the role

What you'll do

• VisionAI)
• What do you need for this opportunity?
• Product Strategy: Own the product vision, roadmap, prioritization, and feature requirements.
• Customer Discovery: Understand enterprise workflows, identify customer pain points, and translate them into product opportunities.
• AI Agents & Automation: Define requirements for building, testing, evaluating, and improving AI agents and automated workflows.
• Technical Collaboration: Work with Engineering and AI teams on APIs, integrations, data flows, security, and platform capabilities.
• Product Execution: Create PRDs, user stories, acceptance criteria, and release plans while coordinating cross-functional teams.
• Scalability & Reusability: Identify recurring customer needs and turn them into reusable product features instead of one-off solutions.
• Product Performance: Track adoption, customer satisfaction, workflow effectiveness, and business impact to guide product improvements.
• Must Haves/ Requirements
• 5+ years of Product Management experience, preferably in B2B SaaS, enterprise platforms, AI products, or workflow automation.
• Strong understanding of APIs, integrations, system architecture, and enterprise workflows.

What you'll bring

• API Connectors, rag, Tool calling, Pdr, B2B SaaS, Workflow automation
• VisionAI is Looking for:
• Live2AI is looking for a technically strong and customer-focused Product Manager to build and scale AI-powered applications, agents, and workflow automation solutions for enterprise customers.
• In this role, you will own product strategy, roadmap, customer discovery, and feature prioritization. You will work closely with Engineering, AI, Design, Sales, and Customer Success teams to translate customer problems into scalable product capabilities that can be reused across multiple customers.
• Experience with AI agent platforms, workflow orchestration, or low-code/no-code tools.
• Familiarity with enterprise security, permissions, governance, and compliance.
• Experience with product analytics, experimentation, and technical prototyping.
• Success Metrics
• Product adoption and sustained usage across enterprise customers.
• Improved AI agent performance, reliability, and task completion.
• Increased reuse of platform capabilities across customers.
• Reduced deployment time and implementation effort.