AI Agent Product Manager, Builder

Hello Patient•Austin, TX

1d•$110,000 - $145,000

About The Position

Hello Patient is hiring an AI Agent Product Manager to build AI voice agents from scratch for healthcare practices. The role designs how agents listen, interpret, respond, and guide patients through healthcare workflows, including conversation structure, language, tool use, transfers, and recovery. It is hands-on: the Product Manager creates prompts, conversation flows, and agent configurations, then uses simulations and real agent conversations to identify and address breakdowns. The role works closely with Engineering and Customer Delivery Product Managers to ensure agents perform reliably in production. The Product Manager owns agent architecture and configuration, translates customer processes and requirements into agent behavior, and partners with Engineering on integrations, features, and testing. They also own agent quality through evaluations, simulations, reviews, and troubleshooting during launch and after go-live. As agents evolve, they remain the architectural owner, support teams after handoff, review changes, lead refactors, and develop reusable components and patterns across deployments.

Requirements

At least 1 year of experience in conversational design, voice user experience, or a closely related field, with hands-on experience building AI agents or conversational systems from scratch.
Experience working closely with voice AI agents, including designing, testing, and refining their behavior in real conversations.
Strong understanding of conversation structure, turn-taking, intent recognition, ambiguity, clarification, and recovery when an interaction goes off track.
Hands-on prompt engineering skills and ability to translate customer workflows into agent instructions, conversation flows, and decision logic.
Ability to review calls and transcripts, identify conversational failure patterns, and turn findings into concrete improvements.
Technical fluency with agent-building platforms, tool calls, APIs, and integrations, including how system constraints affect conversations.
Strong ownership and ability to work across customer-facing and engineering teams in a fast-moving environment.

Nice To Haves

Background in linguistics, computational linguistics, discourse analysis, human-computer interaction, or a related discipline.
Experience shipping voice AI agents into production and improving them using real call data.
Familiarity with speech recognition and text-to-speech systems, including the effects of latency, interruptions, pronunciation, and speech recognition errors on the experience.
Experience building evaluations and simulations for conversational quality and task completion.
Background in healthcare or other environments with complex, sensitive customer interactions.
A portfolio of voice or conversational experiences built, with examples of how testing informed design decisions.

Responsibilities

Design and build production-ready agents, including prompts, intents, conversation flows, tool calls, extensions, transfer protocols, and retrieval-augmented knowledge bases.
Lead technical discovery to translate customer business processes, rules, exceptions, and handoffs into agent behavior.
Build agents that handle healthcare workflows involving scheduling logic, patient context, EHR data, and practice-specific requirements.
Partner with Engineering on integrations, new features, and end-to-end testing, translating integration constraints into agent design decisions.
Assess technical feasibility and help Customer Delivery Product Managers understand implementation effort and tradeoffs before scope and timelines are committed.
Author evaluations, tags, and simulation scenarios covering expected behavior, edge cases, and failure modes.
Build and run simulation suites, review results, and own internal agent quality before customer demos and testing.
Peer-review other builders’ agents and take accountability for technical approvals.
Diagnose issues during soft launch and the initial period after go-live using live conversations, evaluations, and customer feedback.
Determine whether issues require targeted fixes or agent re-architecture.
Author the QA Agent Playbook and prepare Agent Technician and QA teams to support agents after handoff.
Remain the architectural owner of agents built and advise on changes affecting their structure and behavior.
Review Agent Technician pull requests and lead refactors requiring deeper architectural work.
Assess whether expansion requests can use existing features or require new capabilities.
Turn patterns across deployments into reusable components and patterns to accelerate future agent development.