Product Manager - AI Assistant / DB / Support

Key Responsibilities

• AI Assistant Product Strategy: Define and evolve the conversational experience that makes Bondi feel intelligent, helpful, and capable of understanding complex organizational needs
• Customer Needs Translation: Deeply understand B2B customer workflows, pain points, and requirements - then translate them into AI assistant capabilities
• Database & Data Model Design: Shape how Bondi structures, stores, and retrieves organizational data to enable intelligent responses and workflow execution
• Conversational UX: Design dialogue flows, response patterns, clarification mechanisms, and feedback loops that make AI interactions feel natural and productive
• Support Experience: Build the product layer for how users get help, troubleshoot issues, and learn to use Bondi more effectively through the assistant itself
• Workflow Intelligence: Define how the AI assistant guides users through complex multi-step processes, suggests optimizations, and proactively identifies opportunities
• Enterprise Scalability: Ensure the assistant experience works seamlessly for organizations with thousands of workflows, complex data structures, and diverse user roles
• AI Behavior Guidelines: Collaborate with Context Engineers and AI teams to define assistant personality, capabilities, limitations, and handling of edge cases
• Metrics & Learning: Instrument the assistant to track understanding accuracy, task completion rates, user satisfaction, and continuously improve based on data
• Cross-Functional Collaboration: Work with Engineering, AI/ML, Design, and Customer Success to deliver cohesive, delightful experiences

Requirements

Essential Qualifications

• 4+ years of product management experience, with at least 2 years on AI/conversational products or B2B SaaS platforms
• Strong understanding of AI/LLM capabilities, limitations, and conversational design patterns
• Experience designing database schemas, data models, or working closely with data architecture
• Deep user research skills - ability to uncover unstated needs and translate them into product requirements
• Track record of shipping B2B products that handle complex workflows and organizational data
• Excellent written communication skills (critical for defining AI behavior and conversation flows)
• Data-driven approach with experience in product analytics and experimentation
• Technical fluency to engage deeply with engineering teams on implementation details

Preferred Qualifications

• Experience building AI assistants, chatbots, or conversational interfaces
• Background in database design, data modeling, or business intelligence tools
• Familiarity with prompt engineering and RAG (Retrieval-Augmented Generation) systems
• Understanding of enterprise support systems and knowledge management
• Previous experience at a B2B SaaS company, especially in workflow automation or data platforms
• UX research or design background
• Startup experience in growth-stage environments

What We're Looking For

• Conversational Design Intuition: You understand what makes AI interactions feel magical vs. frustrating, and can design for natural, productive conversations
• Customer Obsession: You spend time with users, understand their problems deeply, and advocate for their needs throughout the product development process
• Systems Thinking: You see how data structure, AI capabilities, UX, and workflows interconnect to create holistic experiences
• Empathy for Complexity: You understand that organizations are messy, workflows are complex, and edge cases are everywhere — and you design for it
• Iterative Mindset: You ship early versions to learn, gather feedback rapidly, and iterate based on real usage patterns
• Clear Communicator: You can articulate complex AI behavior in simple terms and write specifications that engineers, designers, and stakeholders all understand
• Detail-Oriented: You care about microcopy, error messages, loading states, and all the small touches that define assistant quality
• Collaborative: You work effectively across technical and non-technical teams to align on vision and execution

Key Challenges You'll Solve

• How do we help the AI assistant understand messy, incomplete, or ambiguous user requests?
• What's the right balance between proactive guidance and letting users maintain control?
• How do we structure organizational data so the assistant can intelligently retrieve and use it in context?
• How do we handle errors, misunderstandings, and limitations gracefully without breaking user trust?
• How do we scale the assistant experience from simple queries to orchestrating complex enterprise workflows?
• What support should be human-assisted vs. fully automated through the AI assistant?

Success Metrics

• Task completion rate through conversational interface
• User satisfaction scores (CSAT/NPS for assistant interactions)
• Time-to-value for new users building their first workflows
• Reduction in support tickets through self-service assistant capabilities
• Accuracy of intent understanding and response relevance
• Adoption of advanced assistant features across user base
• Database query efficiency and data retrieval success rates

Why Bondi?

This role sits at the heart of what makes Bondi unique — our ability to let organizations build systems through conversation. You'll define how AI translates human intent into action, how complex data becomes accessible through simple questions, and how we make powerful capabilities feel effortlessly intuitive. If you're passionate about making AI genuinely useful for real business problems, this is your opportunity.