Principal Product Manager - Voice AI

We are hiring a Principal Product Manager to define and lead the next generation of this platform. This person will own the long-term product strategy, architecture, quality bar, evaluation system, commercial model, and operating metrics required to make Voice AI dependable across millions of real-world phone conversations.

This is not a prompt-management or chatbot-feature role. It is a senior individual-contributor product leadership role requiring deep systems thinking across AI, voice, telephony, automation, CRM, reliability, compliance, and business outcomes. You will influence multiple product and engineering teams, make platform-level trade-offs, and establish Voice AI as one of the most trusted and commercially important products in the HighLevel ecosystem.

Responsibilities:

• Define and drive the long-term vision, strategy, roadmap, and platform architecture for HighLevel Voice AI.
• Own the complete Voice AI lifecycle, including agent creation, prompts, system instructions, voice and model selection, knowledge, actions, testing, deployment, phone routing, inbound and outbound calling, transfers, analytics, permissions, APIs, billing, and optimisation.
• Establish the product principles that determine when a Voice AI agent should answer, ask a clarifying question, retrieve knowledge, take an action, transfer to another agent, transfer to a human, schedule follow-up, or end the call.
• Develop a deep understanding of agencies, SMBs, franchises, multi-location businesses, and call-intensive industries such as home services, healthcare and wellness, legal, real estate, automotive, insurance, financial services, fitness, hospitality, and professional services.
• Personally review real call recordings, transcripts, latency traces, action logs, failed calls, support tickets, customer configurations, implementation challenges, and measurable business outcomes.
• Translate ambiguous customer and platform problems into strategic choices, product requirements, system models, phased roadmaps, quality standards, and measurable success criteria.
• Partner closely with engineering and AI leadership on streaming architecture, speech-to-text, text-to-speech, voice activity detection, turn detection, interruption handling, LLM orchestration, tool invocation, context management, retrieval, caching, latency, reliability, model selection, and cost.
• Partner closely with Phone System and infrastructure teams on call routing, number provisioning, carrier integrations, Twilio and LC Phone behaviour, recording, transfers, forwarding, voicemail, call status, and telephony failure modes.
• Establish a scalable evaluation and release framework for model, prompt, voice, retrieval, action, routing, and infrastructure changes.
• Define production service expectations across call-answer rates, connection success, response latency, audio quality, uptime, action reliability, transfer reliability, and graceful degradation.
• Partner with Design to simplify agent creation, voice selection, prompt configuration, testing, deployment, debugging, analytics, optimisation, and reuse.
• Make Prompt Evaluator, Edit with AI, Prompt Optimiser, Web Call testing, phone testing, and production logs part of a coherent agent-quality workflow.
• Improve integrations between Voice AI and Contacts, Conversations, Calendars, Workflows, Opportunities, Knowledge Base, Payments, Custom Fields, Custom Objects, Phone System, and Reporting.
• Define the architecture and customer experience for multi-agent transfers, human transfers, context handoffs, specialist reuse, fallback behaviour, and merged post-call outputs.
• Develop observability and debugging experiences that expose call state, latency, transcripts, retrieved knowledge, model behaviour, tool calls, parameter extraction, action responses, transfers, carrier errors, and execution timelines.
• Define instrumentation across the full funnel, including agent creation, configuration completion, first test, first successful test, number assignment, first live call, first successful action, sustained usage, business outcomes, retention, and expansion.
• Define operational metrics for inbound and outbound Voice AI, distinguishing between dialling, connection, conversation, qualification, execution, transfer, and business-outcome success.
• Partner with Legal, Compliance, Trust, and Security on consent, disclosures, voice cloning, recording, data processing, retention, outbound calling, sensitive information, fraud, abuse, and platform safeguards.
• Partner with Product Marketing on positioning, use cases, competitive differentiation, customer education, vertical templates, launches, and agency enablement.
• Partner with Support, Implementation, Account Management, Trial Experience, Affiliates, and agency-facing teams to reduce setup friction, improve deployment quality, and lower support burden.
• Partner with Finance and Revenue Experience on pricing, included usage, overages, agency rebilling, model costs, telephony costs, gross margin, budget protection, and sustainable commercial limits.
• Drive strategy across the broader AI Employee portfolio so Voice AI works coherently with Conversation AI, Knowledge Base, Agent Studio, Ask AI, Workflows, Calendars, and future AI-agent capabilities.
• Evaluate external models, voice providers, telephony vendors, infrastructure components, and potential strategic partnerships.
• Act as a senior product thought partner to Product, Engineering, Design, Data, GTM, Finance, Legal, and executive leadership.
• Mentor PMs and raise the quality of product strategy, AI evaluation, systems thinking, and decision-making across the organisation without relying on formal authority.

Requirements:

• 12+ years of product management experience owning complex B2B SaaS, Voice AI, conversational AI, communications, contact-centre, telephony, CRM, workflow automation, or AI-agent products. Scope and demonstrated outcomes matter more than a precise number of years.
• Prior experience operating as a Principal PM, Staff PM, Lead PM, product founder, or equivalent senior individual contributor responsible for a business-critical product or platform.
• Evidence of defining strategy across multiple teams and delivering sustained customer and commercial outcomes, not only shipping individual features.
• Experience building or operating production AI-agent systems that interact with real customers and take actions inside business workflows.
• Strong understanding of the difference between an impressive voice demonstration and a reliable production calling product.
• Strong judgment around AI evaluation, able to define how voice agents should be tested, scored, monitored, debugged, and improved in production.
• Strong systems thinking, able to connect phone infrastructure, AI models, voices, prompts, CRM data, calendars, workflows, actions, permissions, reporting, compliance, and billing into a coherent product.
• Experience simplifying technically sophisticated systems for non-technical customers.
• Experience working with multi-tenant SaaS and the operational requirements of agencies, franchises, resellers, or multi-location businesses.
• Strong customer instincts and willingness to inspect recordings, transcripts, traces, failed calls, implementation issues, and support data personally.
• Commercial judgment across activation, retention, packaging, usage-based pricing, provider cost, telephony cost, gross margin, and partner economics.
• Ability to make difficult trade-offs between caller experience, latency, accuracy, reliability, extensibility, compliance, and cost.
• Ability to influence senior stakeholders and multiple teams without relying on direct reporting authority.
• Excellent written communication, able to produce clear strategy documents, product requirements, system models, evaluation plans, architectural decisions, executive updates, and launch narratives.
• High ownership, intellectual honesty, and execution velocity in a remote-first, high-context environment.

Technical fluency across several of the following:

• Speech-to-text and automatic speech recognition
• Text-to-speech and voice models
• Streaming audio
• Voice activity and end-of-turn detection
• Barge-in and interruption handling
• Noise and echo cancellation
• LLM orchestration and function calling
• Context management and RAG/knowledge retrieval
• APIs and webhooks
• Telephony, PSTN, SIP, or carrier infrastructure
• Latency, reliability, observability, and cost

Bonus Points For:

• Experience building production voice agents, contact-centre AI, automated receptionists, sales dialers, or customer-service voice automation.
• Experience with voice and AI platforms such as Twilio, ElevenLabs, Cartesia, Deepgram, Google, OpenAI, Anthropic, Amazon Connect, Genesys, Five9 Dialpad, RingCentral, or similar technologies.
• Experience with PSTN, SIP, WebRTC, IVR, call routing, caller identification, number provisioning, recording, voicemail detection, and carrier failure modes.
• Experience building real-time systems with strict latency and availability requirements.
• Experience designing agent tools, function calling, MCP integrations, workflow actions, or external API execution.
• Experience building automated evaluation systems using scenario generation, synthetic callers, human review, production telemetry, transcripts, recordings, and business-outcome data.
• Experience with appointment scheduling, lead qualification, customer support, call routing, outbound campaigns, or service-dispatch products.
• Experience supporting multilingual speech recognition and synthesis, accents, localisation, translation, pronunciation, or voice cloning.
• Experience with consent, AI disclosure, call recording, opt-out management, outbound-contact rules, trust and safety, or communications-platform abuse prevention.
• Experience building APIs, webhooks, developer platforms, reusable templates, marketplaces, or partner ecosystems.
• Experience building products for agencies, SMBs, franchises, local businesses, or multi-location operators.
• Experience with AI usage-based pricing, per-minute communication pricing, provider routing, model cost management, gross-margin optimisation, rebilling, or fair-use controls.
• Familiarity with metrics such as call answer rate, connection rate, time to first response, end-of-turn latency, barge-in success, speech-recognition accuracy, call completion rate, containment rate, transfer success rate, action success rate, appointment-booking conversion, caller sentiment, opt-out and complaint rate, P95/P99 latency, cost per call, cost per successful outcome, retention, and support-ticket rate.