Principal Product Manager - Knowledge Bases & Ask AI

Responsibilities

• Define and drive the long-term product vision, strategy, roadmap, and platform architecture for HighLevel Knowledge Bases and Ask AI.
• Own the complete Ask AI experience, including chat, voice interaction, conversation history, memory, templates, artefacts, scheduled tasks, tools, actions, agent routing, browser interaction, feedback, permissions, approvals, auditability, usage, and lifecycle management.
• Own the Knowledge Base platform across source ingestion, extraction, parsing, chunking, embeddings, indexing, metadata, retrieval, re-ranking, citations, freshness, versioning, testing, permissions, and observability.
• Establish product principles for answering questions, retrieving knowledge, generating plans, selecting tools, invoking agents, requesting approval, executing actions, handling failures, and communicating results.
• Create a shared context model spanning identity, agency, location, role, permissions, interface context, business profile, Brand Voice, memory, Knowledge Bases, CRM data, product configuration, and previous tool outputs.
• Develop a deep understanding of agency owners, marketers, sales teams, customer-service teams, operations leaders, administrators, and SMB employees.
• Inspect Ask AI conversations, tool traces, Knowledge Base retrieval results, user feedback, support tickets, ingestion failures, incorrect answers, failed actions, and downstream customer outcomes.
• Partner with AI, engineering, platform, infrastructure, product, and design teams on orchestration, model routing, context management, prompts, tools, agents, memory, retrieval-augmented generation, embeddings, search, re-ranking, caching, latency, evaluation, observability, cost, ingestion, storage, indexing, reliability, and retention.
• Define evaluation architecture and representative test datasets covering responses, retrieval, memory, tool selection, action accuracy, permissions, artefacts, latency, and cost.
• Establish shared contracts and onboarding models for product teams contributing actions, templates, skills, artefacts, or specialized agents.
• Advance integration between Ask AI and Agent Studio.
• Define the platform model for MCP tools, native actions, external APIs, web search, browser execution, Knowledge Base retrieval, and other agent capabilities.
• Build observability and debugging experiences covering context, sources, outputs, plans, tools, permissions, approvals, results, errors, latency, and usage.
• Improve Knowledge Base quality-management workflows, including retrieval testing, source inspection, stale-content detection, crawl diagnostics, processing errors, conflict detection, and recommendations.
• Define reusable, inherited, bundled, and marketplace-distributed Knowledge Bases across agencies and locations.
• Partner with Design on Knowledge Base creation, source management, testing, maintenance, agent attachment, onboarding, templates, approvals, artefacts, and error recovery.
• Develop a coherent experience across templates, open-ended prompting, guided questions, native skills, specialized agents, and scheduled tasks.
• Define instrumentation across the full funnel.

Requirements and Qualifications

• Principal-level product leadership experience building platform products.
• Experience with AI assistants, enterprise knowledge, retrieval systems, agent orchestration, workflow execution, CRM data, permissions, automation, developer platforms, and multi-tenant SaaS.
• Strong understanding of LLM orchestration, model routing, context management, prompt systems, tool invocation, agent planning, memory, retrieval-augmented generation, embeddings, hybrid search, re-ranking, caching, latency, evaluation, observability, and cost.
• Ability to influence multiple product and engineering teams and establish shared platform standards.
• Deep customer understanding across agencies, marketers, sales, customer service, operations, administrators, and SMB users.

Nice to Have

• Experience with MCP tools, browser execution, vector storage, structured-data retrieval, marketplace distribution, or agent platforms.
• Experience defining governance, quality systems, commercial strategy, and developer onboarding models for AI platforms.