● Define and drive the long-term product vision, strategy, roadmap, and product architecture for HighLevel Conversation AI.
● Own the complete Conversation AI system, including agent creation, prompts, knowledge, actions, visual flows, channel deployment, routing, testing, monitoring, permissions, templates, APIs, and lifecycle management.
● Establish the product principles that determine when Conversation AI should answer, ask a clarifying question, take an action, transfer to another agent, follow up later, or hand the conversation to a human.
● Develop a deep understanding of agencies, SMBs, multi-location businesses, and conversation-heavy industries such as home services, legal, dental, medical and wellness, real estate, insurance, automotive, fitness, and professional services.
● Spend significant time reviewing real customer conversations, AI failures, support tickets, agent configurations, implementation challenges, and measurable customer outcomes.
● Translate ambiguous customer and platform problems into clear strategic choices, product requirements, decision documents, system models, phased roadmaps, and measurable success criteria.
● Partner closely with Engineering and AI leadership on LLM orchestration, model selection, context management, tool invocation, retrieval, re-ranking, latency, caching, reliability, evaluation, observability, data architecture, and cost.
● Build a scalable evaluation framework covering grounded accuracy, action accuracy, instruction adherence, safety, escalation quality, conversation quality, and business outcomes.
● Define testing and release standards for changes to models, prompts, retrieval systems, agent tools, routing logic, and conversation behaviour.
● Partner with Design to simplify the entire agent lifecycle — discovery, creation, configuration, training, testing, deployment, debugging, optimisation, and reuse.
● Create a coherent product experience across guided forms, prompt-based agents, flow-based agents, templates, snapshots, and Ask AI-assisted creation.
● Improve integrations between Conversation AI and Contacts, Conversations, Calendars, Workflows, Opportunities, Payments, Knowledge Base, Custom Fields, Custom Objects, and Reporting.
● Define the platform model for multiple agents, channel assignments, routing priorities, bot transfers, context preservation, and human handovers.
● Develop robust observability and debugging experiences that show conversation context, model responses, retrieved knowledge, tool calls, action inputs and outputs, latency, errors, and execution timelines.
● Define instrumentation across the complete product funnel, including agent creation, training, testing, deployment, first successful conversation, first successful action, ongoing usage, customer outcomes, retention, and expansion.
● Own product decisions involving privacy, data retention, access controls, consent, opt-outs, sensitive information, channel policies, model behaviour, and abuse prevention.
● Partner with Product Marketing on positioning, packaging, use cases, competitive differentiation, launch strategy, customer education, and agency enablement.
● Partner with Support, Implementation, Trial Experience, Account Management, and Affiliates to reduce setup friction, improve customer outcomes, lower support burden, and make Conversation AI easier to sell and implement.
● Partner with Finance and Revenue Experience on subscription plans, usage-based pricing, agency rebilling, AI costs, gross-margin targets, and commercially sustainable product limits.
● Influence product strategy across the broader AI Employee organisation, ensuring that Conversation AI works coherently with Voice AI, Ask AI, Knowledge Base, Agent Studio, Workflow AI, Reviews AI, and future AI products.
● Act as a senior product thought partner to Product, Engineering, Design, Data, GTM, and executive leadership.
● Mentor PMs and raise the quality of product thinking, AI evaluation, strategy, and decision-making across the organisation without relying on formal authority.