Principal Product Manager - Conversation AI

Responsibilities

• Define and drive the long-term product vision, strategy, roadmap, and product architecture for 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 product principles governing when Conversation AI answers, asks clarifying questions, takes actions, transfers between agents, follows up, or hands conversations to humans.
• Develop deep understanding of agencies, SMBs, multi-location businesses, and conversation-heavy industries.
• Review customer conversations, AI failures, support tickets, agent configurations, implementation challenges, and customer outcomes.
• Translate ambiguous customer and platform problems into product requirements, decision documents, system models, roadmaps, and measurable success criteria.
• Partner 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 evaluation frameworks covering grounded accuracy, action accuracy, instruction adherence, safety, escalation quality, conversation quality, and business outcomes.
• Define testing and release standards for models, prompts, retrieval systems, agent tools, routing logic, and conversation behavior.
• Partner with Design to simplify agent discovery, creation, configuration, training, testing, deployment, debugging, optimization, and reuse.
• Create a coherent experience across guided forms, prompt-based agents, flow-based agents, templates, snapshots, and AI-assisted creation.
• Improve integrations with 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 observability and debugging experiences for conversation context, model responses, retrieved knowledge, tool calls, action inputs and outputs, latency, errors, and execution timelines.
• Define instrumentation across agent creation, training, testing, deployment, first successful conversation, first successful action, usage, customer outcomes, retention, and expansion.
• Own decisions involving privacy, data retention, access controls, consent, opt-outs, sensitive information, channel policies, model behavior, and abuse prevention.
• Partner with Product Marketing on positioning, packaging, use cases, competitive differentiation, launches, customer education, and agency enablement.
• Partner with Support, Implementation, Trial Experience, Account Management, and Affiliates to reduce setup friction, improve outcomes, lower support burden, and improve sales and implementation.
• Partner with Finance and Revenue Experience on subscription plans, usage-based pricing, agency rebilling, AI costs, margins, and product limits.
• Influence strategy across the broader AI Employee organization and ensure coherence with Voice AI, Ask AI, Knowledge Base, Agent Studio, Workflow AI, Reviews AI, and future AI products.
• Act as a senior product thought partner across Product, Engineering, Design, Data, GTM, and executive leadership.
• Mentor PMs and improve product thinking, AI evaluation, strategy, and decision-making.

Requirements

• 12+ years of product management experience owning complex B2B SaaS, AI-agent, communications, CRM, or workflow-automation products.
• Senior individual-contributor product leadership experience influencing multiple product and engineering teams.
• Experience defining strategy, architecture, quality systems, operating metrics, and commercial models for complex platforms.
• Experience with AI agents, CRM, messaging infrastructure, workflow automation, knowledge retrieval, appointment scheduling, analytics, developer platforms, or related systems.
• Ability to make platform-level trade-offs and convert ambiguous problems into clear product decisions and measurable outcomes.
• Strong collaboration skills across Engineering, AI, Design, Data, GTM, Finance, Support, and executive leadership.

Nice to Have

• Experience serving agencies, SMBs, multi-location businesses, or conversation-heavy industries.
• Experience with LLM orchestration, model evaluation, retrieval, tool invocation, observability, and AI safety.
• Experience with usage-based pricing, agency rebilling, AI cost management, or SaaS commercialization.
• Experience with multi-agent systems, messaging channels, human handoffs, workflow automation, or appointment scheduling.