[Hiring] Principal Product Manager - Knowledge Bases & Ask AI @HighLevel

Role Description

HighLevel is hiring a Principal Product Manager to own the long-term product strategy for the Ask AI platform. This role involves defining the architecture, product principles, quality systems, developer model, governance, metrics, and commercial strategy required to make Ask AI the default way users understand and operate HighLevel.

This is not a generic chatbot or content-generation role. It is a senior individual-contributor product leadership role at the intersection of:

• AI assistants
• Enterprise knowledge
• Retrieval systems
• Agent orchestration
• Workflow execution
• CRM data
• Permissions
• Automation
• Developer platforms
• Multi-tenant SaaS

You will influence multiple product and engineering teams, establish shared platform standards, and make foundational decisions that affect every AI product across HighLevel.

Key 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 the product principles that determine how Ask AI answers questions, requests more information, retrieves knowledge, generates a plan, selects a tool, invokes an agent, asks for approval, executes an action, handles failure, and communicates results.
• Create a shared context model spanning user identity, agency, location, role, permissions, current interface, 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 who use HighLevel to perform daily work.
• Personally inspect Ask AI conversations, tool traces, Knowledge Base retrieval results, user feedback, support tickets, source-ingestion failures, incorrect answers, failed actions, and downstream customer outcomes.
• Partner closely with AI and engineering leadership on 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.
• Partner with platform and infrastructure teams on ingestion pipelines, crawlers, document processing, vector storage, structured-data retrieval, indexing, refresh jobs, multi-tenant isolation, scalability, reliability, and data retention.
• Define an evaluation architecture covering Ask AI responses, Knowledge Base retrieval, memory usage, tool selection, action accuracy, permissions, artefacts, latency, and cost.
• Build representative test datasets from real agency and SMB use cases across industries, account types, languages, data structures, and product workflows.
• Partner with HighLevel product teams to expose their capabilities safely through Ask AI using shared action, permission, approval, error, and result contracts.
• Establish a scalable onboarding model for product teams that want to contribute Ask AI actions, templates, skills, artefacts, or specialised agents.
• Advance integration between Ask AI and Agent Studio so custom agents can be discovered, selected, invoked, monitored, and improved from a unified Ask AI experience.
• Define the platform model for MCP tools, native product actions, external APIs, web search, browser execution, Knowledge Base retrieval, and other agent capabilities.
• Build robust observability and debugging experiences that show selected context, retrieved sources, model outputs, plans, tools, inputs, permissions, approvals, action results, errors, latency, and usage.
• Improve Knowledge Base quality-management workflows, including retrieval testing, source inspection, stale-content detection, crawl diagnostics, document-processing errors, conflict detection, and customer-facing recommendations.
• Define the architecture for reusable, inherited, bundled, and marketplace-distributed Knowledge Bases across agencies and locations.
• Partner with Design to simplify Knowledge Base creation, source addition, testing, maintenance, agent attachment, Ask AI onboarding, template discovery, approval flows, artefact interaction, and error recovery.
• Develop a coherent experience across Ask AI templates, open-ended prompting, guided questions, native skills, specialised agents, and scheduled tasks.
• Define instrumentation across the full funnel, including Ask AI discovery, first prompt, first useful response, first successful action, repeat usage, template completion, scheduled-task retention, Knowledge Base creation, source ingestion, retrieval tests, agent attachment, and sustained production usage.
• Define quality and outcome metrics by request type rather than treating every Ask AI interaction as equivalent.
• Partner with Security, Legal, Privacy, and Trust teams on data isolation, access control, memory, browser automation, sensitive data, source permissions, content retention, external-model processing, audit logs, and abuse prevention.
• Establish standards for destructive actions, bulk changes, financial operations, external communication, and compliance-sensitive workflows.
• Partner with Product Marketing on positioning, use-case packaging, customer education, competitive differentiation, launches, templates, and agency enablement.
• Partner with Support, Implementation, Trial Experience, Account Management, Affiliates, and internal operations teams to reduce setup friction, improve outcomes, and lower support burden.
• Partner with Finance and Revenue Experience on packaging, pay-per-use pricing, AI Employee plans, agency rebilling, cost controls, gross margin, and commercial limits.
• Develop a clear competitive understanding of AI copilots, enterprise search, AI workspaces, CRM assistants, agent platforms, browser agents, knowledge-management products, and workflow-automation tools.
• Evaluate external model providers, search and retrieval technologies, document-processing systems, vector databases, re-ranking systems, browser technologies, and strategic partnerships.
• Influence strategy across Conversation AI, Voice AI, Agent Studio, Workflow AI, CRM, automation, communications, commerce, and the broader HighLevel platform.
• Act as a senior product thought partner to Product, Engineering, Design, Data, Security, GTM, Finance, and executive leadership.
• Mentor PMs and raise the quality of AI product strategy, platform thinking, evaluation, and decision-making across the organisation without relying on formal authority.

Qualifications

• 12+ years of product management experience owning complex B2B SaaS, AI-assistant, enterprise-search, knowledge-management, workflow-automation, CRM, developer-platform, or AI-agent products.
• Prior experience operating as a Principal PM, Staff PM, Lead PM, product founder, or equivalent senior individual contributor responsible for a business-critical platform.
• Evidence of defining strategy across multiple teams and delivering sustained customer and commercial outcomes.
• Experience building production AI products that combine answers, context, tools, workflows, and actions.
• Strong understanding of the distinction between various AI concepts and their applications.
• Technical fluency across several AI-related technologies and methodologies.
• Strong judgment around AI evaluation and systems thinking.
• Experience designing products where AI can change business data or execute consequential actions.
• Strong instincts around permissions, approvals, auditability, reversibility, sensitive information, and customer trust.
• Experience simplifying technically sophisticated systems for non-technical users.
• Experience with multi-tenant SaaS and the operational needs of various business models.
• Strong customer instincts and willingness to personally inspect outputs and configurations.
• Strong analytical capability to diagnose various failures and issues.
• Commercial judgment across various business metrics.
• Ability to influence multiple senior teams without relying on direct reporting authority.
• Excellent written communication skills.
• High ownership, intellectual honesty, and execution velocity in a remote-first environment.
• Comfortable making difficult prioritisation decisions.

Bonus Points For

• Experience building AI copilots, enterprise assistants, or natural-language interfaces.
• Experience with retrieval architectures and document ingestion pipelines.
• Experience with structured-data question answering and analytics copilots.
• Experience designing memory or personalisation systems.
• Experience building agent-tool ecosystems and evaluation systems.
• Experience with permission-aware AI systems and scheduled agents.
• Experience with rich AI outputs and browser automation.
• Experience building products similar to notable AI platforms.
• Experience building APIs, developer tools, or partner ecosystems.
• Experience building for various business models and familiarity with AI pricing metrics.

Benefits

• Exciting and dynamic work environment.
• Collective responsibility where no task is considered someone else's job.
• Focus on providing value to users through swift delivery of solutions.
• High standard of innovation with continuous improvement.
• Well-funded and profitable company.
• Opportunity to learn the intricacies of scaling a B2B SaaS startup.

EEO Statement

The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide demographic information for compliance purposes. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status.

We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.