AI Agent Product Manager

About the role

Hello Patient is hiring a technical, high-agency AI Agent Product Manager to own the end-to-end delivery of AI agents in real customer environments. We build AI-powered voice, sms, and chat agents that integrate deeply into how healthcare practices actually operate. Every new customer deployment is a product launch-new workflows, new edge cases, new integration requirements, new ways the agent needs to behave in the real world. This role exists to own that launch from scoping through go-live. You'll also own the customer-facing roadmap for each deployment-defining requirements, sequencing what gets built, and aligning stakeholders on tradeoffs. This role combines product ownership with hands-on agent building - translating requirements into shipped agent behavior. You'll gather requirements directly from customers, translate them into agent logic and workflows, and implement that behavior hands-on using prompts, guardrails, tools, and evals. You'll design Mia's behavior, ship production-ready multi-agent workflows, and turn real-world healthcare complexity into systems that actually hold up on live calls. This is a rare seat: you'll get direct exposure to frontier LLM failure modes in production, and you'll continuously iterate on agent performance using structured evaluation, testing, and real customer feedback.

Responsibilities

• Own customer deployments end-to-end
• Lead delivery of net-new AI agent deployments as the single accountable owner-from customer requirements through production go-live
• Treat every deployment as a product launch: define scope, manage tradeoffs, hit timelines, ensure quality
• Own the customer-facing roadmap for each deployment-what are we shipping, in what order, and why
• Build agents, not just specs
• Gather requirements directly from customers and translate them into agent behavior yourself using our internal platform-prompts, tools, guardrails, multi-agent workflows
• Do hands-on prompt engineering using AI tools to build the components that make agents work: conversation flows, decision logic, edge case handling, integration behaviors
• Ship production-ready agents that handle real healthcare complexity: scheduling logic, patient context, EMR data, practice-specific edge cases
• Continuously improve agent performance using structured evals, live call review, and direct customer feedback
• Drive zero-to-one execution
• Lead deployments for new workflows, integrations, and verticals where no playbook exists
• Identify unknowns early, derisk them, and make tradeoff decisions that keep launches on track
• When deployments require net-new platform capabilities, own requirements and prioritization with the engineering team
• Work alongside Conversational Design and Customer Engineering
• Conversational designers design and optimize agent behavior-they review real conversations, identify patterns, design conversation flows, and ship agent behavior
• Customer engineers build integrations into our customers' systems of record-EHRs, PMS, and PIMS
• You own everything else: integration scoping with Customer Engineering, cross-team coordination, timeline management, stakeholder communication, and unblocking whatever's in the way
• Build toward repeatability
• Identify patterns across launches and codify them into playbooks
• Know when a workflow or integration is ready to transition from zero-to-one ownership to steady-state implementation
• Hand off proven patterns to implementation teams and move on to the next net-new challenge

Requirements

• 1+ years in Product Management or a closely related role (e.g., technical program management at a product-led company, founder/early employee wearing the PM hat) or a technical background (software engineer / forward-deployed engineer) who has operated in a PM-like capacity
• Strong technical product background-comfortable with APIs, integrations, and understanding how systems connect
• Experience shipping in ambiguous, fast-moving environments where the playbook doesn't exist yet
• Proven ability to work across functions through influence, not authority
• Bias toward ownership and action-you'd rather make a call and course-correct than wait for clarity
• Experience with AI-native products, agents, LLMs, or automation platforms including hands-on prompt/agent buildingBackground in healthcare, revenue cycle, or other legacy-system-heavy industries
• You've spent time playing with bots - building them, breaking them, and tweaking conversations to make them feel more natural.
• Founder, co-founder, or early startup experience
• Familiarity with voice AI or real-time orchestration systems
• Portfolio or examples of shipped conversational experiences (IVR, voice assistants, chatbots, SMS flows) and the rationale behind key design decisions
• Familiarity with evaluation practices for agent quality

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